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{
"cells": [
{
"attachments": {},
"cell_type": "markdown",
"metadata": {},
"source": [
"# Testing the Forrest\n",
"\n",
"## Importing the Basics"
]
},
{
"cell_type": "code",
"execution_count": 1,
"metadata": {},
"outputs": [],
"source": [
"import numpy as np\n",
"import random\n",
"from matplotlib import pyplot as plt\n",
"from metric import ConfusionMatrix, RegressionScores\n",
"from utility import ModelIO\n",
"from rf import (\n",
" RandomForest, DecisionTree,\n",
" Gini, Entropy, MAE, MSE,\n",
" Mode, Mean, Confidence,\n",
" CART, ID3, C45,\n",
" AdaBoosting, GradientBoosting,\n",
" Majority, Confidence, Average, Median\n",
")"
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]
},
{
"attachments": {},
"cell_type": "markdown",
"metadata": {},
"source": [
"## Generating Test Data\n",
"\n",
"Here I generate random test data. It's two blocks shifted very slightly in some dimensions. For classifier tasks each block gets a label, for regressor tasks each block gets the average coordinates plus some random value as a traget. It's a very simple dummy data set meant for testing the code.\n",
"\n",
"Here one can change the dimensionallity and amount of the data."
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {},
"outputs": [],
"source": [
"def dataShift(dims):\n",
" offSet = [5, 1.5, 2.5]\n",
" diffLen = abs(len(offSet) - dims)\n",
" offSet.extend([0] * diffLen)\n",
" random.shuffle(offSet)\n",
" return offSet[:dims]\n",
"\n",
"# Initialize some parameters\n",
"totalAmount = 6400\n",
"dims = 5\n",
"evalAmount = totalAmount // 4\n",
"trainAmount = totalAmount - evalAmount\n",
"offSet = dataShift(dims)\n",
"\n",
"# Create covariance matrix\n",
"cov = np.eye(dims) # This creates a covariance matrix with variances 1 and covariances 0\n",
"\n",
"# Generate random multivariate data\n",
"oneData = np.random.multivariate_normal(np.zeros(dims), cov, totalAmount)\n",
"twoData = np.random.multivariate_normal(offSet, cov, totalAmount)\n",
"\n",
"# Split the data into training and evaluation sets\n",
"trainData = np.vstack((oneData[:trainAmount], twoData[:trainAmount]))\n",
"validData = np.vstack((oneData[trainAmount:], twoData[trainAmount:]))\n",
"\n",
"# Labels for classification tasks\n",
"trainLabels = np.hstack((np.zeros(trainAmount), np.ones(trainAmount)))\n",
"validLabels = np.hstack((np.zeros(evalAmount), np.ones(evalAmount)))\n",
"\n",
"# Targets for regression tasks\n",
"trainTargets = np.sum(trainData, axis=1) + np.random.normal(0, 0.1, 2*trainAmount)\n",
"validTargets = np.sum(validData, axis=1) + np.random.normal(0, 0.1, 2*evalAmount)\n",
"\n",
"# Shuffle the training data\n",
"trainIndex = np.random.permutation(len(trainData))\n",
"trainData = trainData[trainIndex]\n",
"trainLabels = trainLabels[trainIndex]"
]
},
{
"attachments": {},
"cell_type": "markdown",
"metadata": {},
"source": [
"## Creating the Forrest\n",
"\n",
"Here the forrest is created. One can set the number of trees and set the maximum depth. Depending on the task, we add a different impurity function and a different leaf function. Finally we add the split algorithm and set the feature percentile. Higher numbers look at more possible splits, but decreases speed. Lower numbers look at less possible splits, speeding up the algorithm. Depending on the data set this can have a strong impact on the performance.\n",
"\n",
"One can set a different depth, leaf function, splitting algorithm and impurity function for each tree. Here in this simple case we create all trees with same parameters."
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {},
"outputs": [],
"source": [
"task = 'classifier' # 'classifier'/'regressor'\n",
"forrest = RandomForest(bootstrapping=False, retrainFirst=False)\n",
"forrest.setComponent(AdaBoosting())\n",
"forrest.setComponent(Majority())\n",
"for i in range(50):\n",
" tree = DecisionTree(maxDepth=7, minSamplesSplit=2)\n",
" if task == 'regressor':\n",
" tree.setComponent(MSE())\n",
" tree.setComponent(Mean())\n",
" elif task == 'classifier':\n",
" tree.setComponent(Entropy())\n",
" tree.setComponent(Mode())\n",
" tree.setComponent(CART(featurePercentile=90))\n",
" forrest.append(tree)"
]
},
{
"attachments": {},
"cell_type": "markdown",
"metadata": {},
"source": [
"## Trainining the tree\n",
"\n",
"Again, depending on the task we train the forrest with targets or labels. Then we make a prediction and plot the tree."
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"tree 01 |\u001b[0m\u001b[31m\u001b[0m\u001b[0m\u001b[31m \u001b[0m | 00%\r"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"tree 01 |⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿| done ✔ | 19%\n",
"tree 02 |⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿| done ✔ | 19%\n",
"tree 03 |⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿| done ✔ | 19%\n",
"tree 04 |⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿| done ✔ | 19%\n",
"tree 05 |⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿| done ✔ | 19%\n",
"tree 06 |⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿| done ✔ | 19%\n",
"tree 07 |⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿| done ✔ | 19%\n",
"tree 08 |⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿| done ✔ | 19%\n",
"tree 09 |⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿| done ✔ | 19%\n",
"tree 10 |⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿| done ✔ | 19%\n",
"tree 11 |⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿| done ✔ | 19%\n",
"tree 12 |⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿| done ✔ | 19%\n",
"tree 13 |⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿| done ✔ | 19%\n",
"tree 14 |⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿| done ✔ | 19%\n",
"tree 15 |⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿| done ✔ | 19%\n",
"tree 16 |⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿| done ✔ | 19%\n",
"tree 17 |⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿| done ✔ | 19%\n",
"tree 18 |⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿| done ✔ | 19%\n",
"tree 19 |⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿| done ✔ | 19%\n",
"tree 20 |⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿| done ✔ | 19%\n",
"tree 21 |⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿| done ✔ | 19%\n",
"tree 22 |⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿| done ✔ | 19%\n",
"tree 23 |⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿| done ✔ | 19%\n",
"tree 24 |⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿| done ✔ | 19%\n",
"tree 25 |⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿| done ✔ | 19%\n",
"tree 26 |⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿| done ✔ | 19%\n",
"tree 27 |⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿| done ✔ | 19%\n",
"tree 28 |⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿| done ✔ | 19%\n",
"tree 29 |⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿| done ✔ | 19%\n",
"tree 30 |⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿| done ✔ | 19%\n",
"tree 31 |⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿| done ✔ | 19%\n",
"tree 32 |⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿| done ✔ | 19%\n",
"tree 33 |⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿| done ✔ | 19%\n",
"tree 34 |⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿| done ✔ | 19%\n",
"tree 35 |⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿| done ✔ | 19%\n",
"tree 36 |⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿| done ✔ | 19%\n",
"tree 37 |⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿| done ✔ | 19%\n",
"tree 38 |⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿| done ✔ | 19%\n",
"tree 39 |⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿| done ✔ | 19%\n",
"tree 40 |⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿| done ✔ | 19%\n",
"tree 41 |⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿| done ✔ | 19%\n",
"tree 42 |⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿| done ✔ | 19%\n",
"tree 43 |⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿| done ✔ | 19%\n",
"tree 44 |⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿| done ✔ | 19%\n",
"tree 45 |⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿| done ✔ | 19%\n",
"tree 46 |⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿| done ✔ | 19%\n",
"tree 47 |⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿| done ✔ | 19%\n",
"tree 48 |⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿| done ✔ | 19%\n",
"tree 49 |⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿| done ✔ | 19%\n",
"tree 50 |⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿| done ✔ | 19%\n",
"━━━━━━━━━━━━━━━━━━━━━━━━━━ forrest ━━━━━━━━━━━━━━━━━━━━━━━━━━\n",
"voting: Majority, booster: AdaBoosting, bootstrapping: False\n",
"\n",
"————————————————————— tree: 01/50 ——————————————————————\n",
"split: CART, impurity: Entropy, leaf: Mode, nodes: 51\n",
"maxDepth: 7, reached depth: 7, minSamplesSplit: 2\n",
"························································\n",
"╴feat: 3 <= 2.20, samples: 9600\n",
" ├─feat: 3 <= 1.99, samples: 4747\n",
" │ ├─feat: 0 <= 1.43, samples: 4694\n",
" │ │ └─╴value: 0.0\n",
" │ │ └─╴feat: 3 <= 1.38, samples: 361\n",
" │ │ ├─feat: 4 <= 1.69, samples: 341\n",
" │ │ │ └─╴value: 0.0\n",
" │ │ │ └─╴feat: 2 <= 0.64, samples: 15\n",
" │ │ │ └─╴value: 0.0\n",
" │ │ │ └─╴value: 1.0\n",
" │ │ └─╴feat: 0 <= 1.90, samples: 20\n",
" │ │ └─╴value: 0.0\n",
" │ │ └─╴feat: 4 <= -0.37, samples: 9\n",
" │ │ └─╴value: 0.0\n",
" │ │ └─╴value: 1.0\n",
" │ └─╴feat: 0 <= 1.10, samples: 53\n",
" │ └─╴value: 0.0\n",
" │ └─╴feat: 3 <= 2.05, samples: 14\n",
" │ └─╴value: 0.0\n",
" │ └─╴feat: 2 <= 1.67, samples: 10\n",
" │ └─╴value: 1.0\n",
" │ └─╴value: 0.0\n",
" └─╴feat: 3 <= 3.17, samples: 4853\n",
" ├─feat: 0 <= 1.21, samples: 214\n",
" │ ├─feat: 4 <= 0.85, samples: 71\n",
" │ │ ├─feat: 0 <= 1.15, samples: 49\n",
" │ │ │ └─╴value: 0.0\n",
" │ │ │ └─╴feat: 3 <= 2.25, samples: 3\n",
" │ │ │ └─╴value: 0.0\n",
" │ │ │ └─╴value: 1.0\n",
" │ │ └─╴feat: 1 <= 1.16, samples: 22\n",
" │ │ ├─feat: 0 <= 0.95, samples: 17\n",
" │ │ │ └─╴value: 0.0\n",
" │ │ │ └─╴value: 1.0\n",
" │ │ └─╴value: 1.0\n",
" │ └─╴feat: 0 <= 2.15, samples: 143\n",
" │ ├─feat: 3 <= 2.68, samples: 43\n",
" │ │ ├─feat: 1 <= -1.04, samples: 20\n",
" │ │ │ └─╴value: 0.0\n",
" │ │ │ └─╴value: 1.0\n",
" │ │ └─╴value: 1.0\n",
" │ └─╴value: 1.0\n",
" └─╴feat: 0 <= 0.16, samples: 4639\n",
" ├─feat: 3 <= 3.46, samples: 51\n",
" │ ├─feat: 0 <= -0.50, samples: 4\n",
" │ │ └─╴value: 1.0\n",
" │ │ └─╴feat: 2 <= -0.75, samples: 3\n",
" │ │ └─╴value: 0.0\n",
" │ │ └─╴value: 0.0\n",
" │ └─╴value: 1.0\n",
" └─╴value: 1.0\n",
"\n",
"————————————————————— tree: 02/50 ——————————————————————\n",
"split: CART, impurity: Entropy, leaf: Mode, nodes: 51\n",
"maxDepth: 7, reached depth: 7, minSamplesSplit: 2\n",
"························································\n",
"╴feat: 3 <= 2.20, samples: 9600\n",
" ├─feat: 3 <= 1.99, samples: 4747\n",
" │ ├─feat: 0 <= 1.43, samples: 4694\n",
" │ │ └─╴value: 0.0\n",
" │ │ └─╴feat: 3 <= 1.38, samples: 361\n",
" │ │ ├─feat: 4 <= 1.69, samples: 341\n",
" │ │ │ └─╴value: 0.0\n",
" │ │ │ └─╴feat: 2 <= 0.64, samples: 15\n",
" │ │ │ └─╴value: 0.0\n",
" │ │ │ └─╴value: 1.0\n",
" │ │ └─╴feat: 0 <= 1.90, samples: 20\n",
" │ │ └─╴value: 0.0\n",
" │ │ └─╴feat: 4 <= -0.37, samples: 9\n",
" │ │ └─╴value: 0.0\n",
" │ │ └─╴value: 1.0\n",
" │ └─╴feat: 0 <= 1.10, samples: 53\n",
" │ └─╴value: 0.0\n",
" │ └─╴feat: 3 <= 2.05, samples: 14\n",
" │ └─╴value: 0.0\n",
" │ └─╴feat: 2 <= 1.67, samples: 10\n",
" │ └─╴value: 1.0\n",
" │ └─╴value: 0.0\n",
" └─╴feat: 3 <= 3.17, samples: 4853\n",
" ├─feat: 0 <= 1.21, samples: 214\n",
" │ ├─feat: 4 <= 0.85, samples: 71\n",
" │ │ ├─feat: 0 <= 1.15, samples: 49\n",
" │ │ │ └─╴value: 0.0\n",
" │ │ │ └─╴feat: 3 <= 2.25, samples: 3\n",
" │ │ │ └─╴value: 0.0\n",
" │ │ │ └─╴value: 1.0\n",
" │ │ └─╴feat: 1 <= 1.16, samples: 22\n",
" │ │ ├─feat: 3 <= 2.86, samples: 17\n",
" │ │ │ └─╴value: 0.0\n",
" │ │ │ └─╴value: 1.0\n",
" │ │ └─╴value: 1.0\n",
" │ └─╴feat: 0 <= 2.15, samples: 143\n",
" │ ├─feat: 3 <= 2.68, samples: 43\n",
" │ │ ├─feat: 1 <= -1.04, samples: 20\n",
" │ │ │ └─╴value: 0.0\n",
" │ │ │ └─╴value: 1.0\n",
" │ │ └─╴value: 1.0\n",
" │ └─╴value: 1.0\n",
" └─╴feat: 0 <= 0.16, samples: 4639\n",
" ├─feat: 3 <= 3.46, samples: 51\n",
" │ ├─feat: 1 <= -0.86, samples: 4\n",
" │ │ └─╴value: 0.0\n",
" │ │ └─╴feat: 1 <= 1.28, samples: 3\n",
" │ │ └─╴value: 1.0\n",
" │ │ └─╴value: 0.0\n",
" │ └─╴value: 1.0\n",
" └─╴value: 1.0\n",
"\n",
"————————————————————— tree: 03/50 ——————————————————————\n",
"split: CART, impurity: Entropy, leaf: Mode, nodes: 51\n",
"maxDepth: 7, reached depth: 7, minSamplesSplit: 2\n",
"························································\n",
"╴feat: 3 <= 2.20, samples: 9600\n",
" ├─feat: 3 <= 1.99, samples: 4747\n",
" │ ├─feat: 0 <= 1.43, samples: 4694\n",
" │ │ └─╴value: 0.0\n",
" │ │ └─╴feat: 3 <= 1.38, samples: 361\n",
" │ │ ├─feat: 4 <= 1.69, samples: 341\n",
" │ │ │ └─╴value: 0.0\n",
" │ │ │ └─╴feat: 2 <= 0.64, samples: 15\n",
" │ │ │ └─╴value: 0.0\n",
" │ │ │ └─╴value: 1.0\n",
" │ │ └─╴feat: 0 <= 1.90, samples: 20\n",
" │ │ └─╴value: 0.0\n",
" │ │ └─╴feat: 4 <= -0.37, samples: 9\n",
" │ │ └─╴value: 0.0\n",
" │ │ └─╴value: 1.0\n",
" │ └─╴feat: 0 <= 1.10, samples: 53\n",
" │ └─╴value: 0.0\n",
" │ └─╴feat: 3 <= 2.05, samples: 14\n",
" │ └─╴value: 0.0\n",
" │ └─╴feat: 2 <= 1.67, samples: 10\n",
" │ └─╴value: 1.0\n",
" │ └─╴value: 0.0\n",
" └─╴feat: 3 <= 3.17, samples: 4853\n",
" ├─feat: 0 <= 1.21, samples: 214\n",
" │ ├─feat: 4 <= 0.85, samples: 71\n",
" │ │ ├─feat: 0 <= 1.15, samples: 49\n",
" │ │ │ └─╴value: 0.0\n",
" │ │ │ └─╴feat: 3 <= 2.25, samples: 3\n",
" │ │ │ └─╴value: 0.0\n",
" │ │ │ └─╴value: 1.0\n",
" │ │ └─╴feat: 1 <= 1.16, samples: 22\n",
" │ │ ├─feat: 3 <= 2.86, samples: 17\n",
" │ │ │ └─╴value: 0.0\n",
" │ │ │ └─╴value: 1.0\n",
" │ │ └─╴value: 1.0\n",
" │ └─╴feat: 0 <= 2.15, samples: 143\n",
" │ ├─feat: 3 <= 2.68, samples: 43\n",
" │ │ ├─feat: 1 <= -1.04, samples: 20\n",
" │ │ │ └─╴value: 0.0\n",
" │ │ │ └─╴value: 1.0\n",
" │ │ └─╴value: 1.0\n",
" │ └─╴value: 1.0\n",
" └─╴feat: 0 <= 0.16, samples: 4639\n",
" ├─feat: 3 <= 3.46, samples: 51\n",
" │ ├─feat: 1 <= -0.86, samples: 4\n",
" │ │ └─╴value: 0.0\n",
" │ │ └─╴feat: 3 <= 3.32, samples: 3\n",
" │ │ └─╴value: 0.0\n",
" │ │ └─╴value: 1.0\n",
" │ └─╴value: 1.0\n",
" └─╴value: 1.0\n",
"\n",
"————————————————————— tree: 04/50 ——————————————————————\n",
"split: CART, impurity: Entropy, leaf: Mode, nodes: 51\n",
"maxDepth: 7, reached depth: 7, minSamplesSplit: 2\n",
"························································\n",
"╴feat: 3 <= 2.20, samples: 9600\n",
" ├─feat: 3 <= 1.99, samples: 4747\n",
" │ ├─feat: 0 <= 1.43, samples: 4694\n",
" │ │ └─╴value: 0.0\n",
" │ │ └─╴feat: 3 <= 1.38, samples: 361\n",
" │ │ ├─feat: 4 <= 1.69, samples: 341\n",
" │ │ │ └─╴value: 0.0\n",
" │ │ │ └─╴feat: 2 <= 0.64, samples: 15\n",
" │ │ │ └─╴value: 0.0\n",
" │ │ │ └─╴value: 1.0\n",
" │ │ └─╴feat: 0 <= 1.90, samples: 20\n",
" │ │ └─╴value: 0.0\n",
" │ │ └─╴feat: 4 <= -0.37, samples: 9\n",
" │ │ └─╴value: 0.0\n",
" │ │ └─╴value: 1.0\n",
" │ └─╴feat: 0 <= 1.10, samples: 53\n",
" │ └─╴value: 0.0\n",
" │ └─╴feat: 3 <= 2.05, samples: 14\n",
" │ └─╴value: 0.0\n",
" │ └─╴feat: 2 <= 1.67, samples: 10\n",
" │ └─╴value: 1.0\n",
" │ └─╴value: 0.0\n",
" └─╴feat: 3 <= 3.17, samples: 4853\n",
" ├─feat: 0 <= 1.21, samples: 214\n",
" │ ├─feat: 4 <= 0.85, samples: 71\n",
" │ │ ├─feat: 0 <= 1.15, samples: 49\n",
" │ │ │ └─╴value: 0.0\n",
" │ │ │ └─╴feat: 2 <= 0.85, samples: 3\n",
" │ │ │ └─╴value: 0.0\n",
" │ │ │ └─╴value: 1.0\n",
" │ │ └─╴feat: 1 <= 1.16, samples: 22\n",
" │ │ ├─feat: 0 <= 0.95, samples: 17\n",
" │ │ │ └─╴value: 0.0\n",
" │ │ │ └─╴value: 1.0\n",
" │ │ └─╴value: 1.0\n",
" │ └─╴feat: 0 <= 2.15, samples: 143\n",
" │ ├─feat: 3 <= 2.68, samples: 43\n",
" │ │ ├─feat: 1 <= -1.04, samples: 20\n",
" │ │ │ └─╴value: 0.0\n",
" │ │ │ └─╴value: 1.0\n",
" │ │ └─╴value: 1.0\n",
" │ └─╴value: 1.0\n",
" └─╴feat: 0 <= 0.16, samples: 4639\n",
" ├─feat: 3 <= 3.46, samples: 51\n",
" │ ├─feat: 1 <= -0.86, samples: 4\n",
" │ │ └─╴value: 0.0\n",
" │ │ └─╴feat: 2 <= 0.21, samples: 3\n",
" │ │ └─╴value: 1.0\n",
" │ │ └─╴value: 0.0\n",
" │ └─╴value: 1.0\n",
" └─╴value: 1.0\n",
"\n",
"————————————————————— tree: 05/50 ——————————————————————\n",
"split: CART, impurity: Entropy, leaf: Mode, nodes: 51\n",
"maxDepth: 7, reached depth: 7, minSamplesSplit: 2\n",
"························································\n",
"╴feat: 3 <= 2.20, samples: 9600\n",
" ├─feat: 3 <= 1.99, samples: 4747\n",
" │ ├─feat: 0 <= 1.43, samples: 4694\n",
" │ │ └─╴value: 0.0\n",
" │ │ └─╴feat: 3 <= 1.38, samples: 361\n",
" │ │ ├─feat: 4 <= 1.69, samples: 341\n",
" │ │ │ └─╴value: 0.0\n",
" │ │ │ └─╴feat: 2 <= 0.64, samples: 15\n",
" │ │ │ └─╴value: 0.0\n",
" │ │ │ └─╴value: 1.0\n",
" │ │ └─╴feat: 0 <= 1.90, samples: 20\n",
" │ │ └─╴value: 0.0\n",
" │ │ └─╴feat: 4 <= -0.37, samples: 9\n",
" │ │ └─╴value: 0.0\n",
" │ │ └─╴value: 1.0\n",
" │ └─╴feat: 0 <= 1.10, samples: 53\n",
" │ └─╴value: 0.0\n",
" │ └─╴feat: 3 <= 2.05, samples: 14\n",
" │ └─╴value: 0.0\n",
" │ └─╴feat: 2 <= 1.67, samples: 10\n",
" │ └─╴value: 1.0\n",
" │ └─╴value: 0.0\n",
" └─╴feat: 3 <= 3.17, samples: 4853\n",
" ├─feat: 0 <= 1.21, samples: 214\n",
" │ ├─feat: 4 <= 0.85, samples: 71\n",
" │ │ ├─feat: 0 <= 1.15, samples: 49\n",
" │ │ │ └─╴value: 0.0\n",
" │ │ │ └─╴feat: 0 <= 1.17, samples: 3\n",
" │ │ │ └─╴value: 1.0\n",
" │ │ │ └─╴value: 0.0\n",
" │ │ └─╴feat: 1 <= 1.16, samples: 22\n",
" │ │ ├─feat: 0 <= 0.95, samples: 17\n",
" │ │ │ └─╴value: 0.0\n",
" │ │ │ └─╴value: 1.0\n",
" │ │ └─╴value: 1.0\n",
" │ └─╴feat: 0 <= 2.15, samples: 143\n",
" │ ├─feat: 3 <= 2.68, samples: 43\n",
" │ │ ├─feat: 1 <= -1.04, samples: 20\n",
" │ │ │ └─╴value: 0.0\n",
" │ │ │ └─╴value: 1.0\n",
" │ │ └─╴value: 1.0\n",
" │ └─╴value: 1.0\n",
" └─╴feat: 0 <= 0.16, samples: 4639\n",
" ├─feat: 3 <= 3.46, samples: 51\n",
" │ ├─feat: 0 <= -0.50, samples: 4\n",
" │ │ └─╴value: 1.0\n",
" │ │ └─╴feat: 1 <= -0.87, samples: 3\n",
" │ │ └─╴value: 0.0\n",
" │ │ └─╴value: 0.0\n",
" │ └─╴value: 1.0\n",
" └─╴value: 1.0\n",
"\n",
"————————————————————— tree: 06/50 ——————————————————————\n",
"split: CART, impurity: Entropy, leaf: Mode, nodes: 51\n",
"maxDepth: 7, reached depth: 7, minSamplesSplit: 2\n",
"························································\n",
"╴feat: 3 <= 2.20, samples: 9600\n",
" ├─feat: 3 <= 1.99, samples: 4747\n",
" │ ├─feat: 0 <= 1.43, samples: 4694\n",
" │ │ └─╴value: 0.0\n",
" │ │ └─╴feat: 3 <= 1.38, samples: 361\n",
" │ │ ├─feat: 4 <= 1.69, samples: 341\n",
" │ │ │ └─╴value: 0.0\n",
" │ │ │ └─╴feat: 2 <= 0.64, samples: 15\n",
" │ │ │ └─╴value: 0.0\n",
" │ │ │ └─╴value: 1.0\n",
" │ │ └─╴feat: 0 <= 1.90, samples: 20\n",
" │ │ └─╴value: 0.0\n",
" │ │ └─╴feat: 4 <= -0.37, samples: 9\n",
" │ │ └─╴value: 0.0\n",
" │ │ └─╴value: 1.0\n",
" │ └─╴feat: 0 <= 1.10, samples: 53\n",
" │ └─╴value: 0.0\n",
" │ └─╴feat: 3 <= 2.05, samples: 14\n",
" │ └─╴value: 0.0\n",
" │ └─╴feat: 2 <= 1.67, samples: 10\n",
" │ └─╴value: 1.0\n",
" │ └─╴value: 0.0\n",
" └─╴feat: 3 <= 3.17, samples: 4853\n",
" ├─feat: 0 <= 1.21, samples: 214\n",
" │ ├─feat: 4 <= 0.85, samples: 71\n",
" │ │ ├─feat: 0 <= 1.15, samples: 49\n",
" │ │ │ └─╴value: 0.0\n",
" │ │ │ └─╴feat: 3 <= 2.25, samples: 3\n",
" │ │ │ └─╴value: 0.0\n",
" │ │ │ └─╴value: 1.0\n",
" │ │ └─╴feat: 1 <= 1.16, samples: 22\n",
" │ │ ├─feat: 3 <= 2.86, samples: 17\n",
" │ │ │ └─╴value: 0.0\n",
" │ │ │ └─╴value: 1.0\n",
" │ │ └─╴value: 1.0\n",
" │ └─╴feat: 0 <= 2.15, samples: 143\n",
" │ ├─feat: 3 <= 2.68, samples: 43\n",
" │ │ ├─feat: 1 <= -1.04, samples: 20\n",
" │ │ │ └─╴value: 0.0\n",
" │ │ │ └─╴value: 1.0\n",
" │ │ └─╴value: 1.0\n",
" │ └─╴value: 1.0\n",
" └─╴feat: 0 <= 0.16, samples: 4639\n",
" ├─feat: 3 <= 3.46, samples: 51\n",
" │ ├─feat: 1 <= -0.86, samples: 4\n",
" │ │ └─╴value: 0.0\n",
" │ │ └─╴feat: 2 <= 0.21, samples: 3\n",
" │ │ └─╴value: 1.0\n",
" │ │ └─╴value: 0.0\n",
" │ └─╴value: 1.0\n",
" └─╴value: 1.0\n",
"\n",
"————————————————————— tree: 07/50 ——————————————————————\n",
"split: CART, impurity: Entropy, leaf: Mode, nodes: 51\n",
"maxDepth: 7, reached depth: 7, minSamplesSplit: 2\n",
"························································\n",
"╴feat: 3 <= 2.20, samples: 9600\n",
" ├─feat: 3 <= 1.99, samples: 4747\n",
" │ ├─feat: 0 <= 1.43, samples: 4694\n",
" │ │ └─╴value: 0.0\n",
" │ │ └─╴feat: 3 <= 1.38, samples: 361\n",
" │ │ ├─feat: 4 <= 1.69, samples: 341\n",
" │ │ │ └─╴value: 0.0\n",
" │ │ │ └─╴feat: 2 <= 0.64, samples: 15\n",
" │ │ │ └─╴value: 0.0\n",
" │ │ │ └─╴value: 1.0\n",
" │ │ └─╴feat: 0 <= 1.90, samples: 20\n",
" │ │ └─╴value: 0.0\n",
" │ │ └─╴feat: 4 <= -0.37, samples: 9\n",
" │ │ └─╴value: 0.0\n",
" │ │ └─╴value: 1.0\n",
" │ └─╴feat: 0 <= 1.10, samples: 53\n",
" │ └─╴value: 0.0\n",
" │ └─╴feat: 3 <= 2.05, samples: 14\n",
" │ └─╴value: 0.0\n",
" │ └─╴feat: 2 <= 1.67, samples: 10\n",
" │ └─╴value: 1.0\n",
" │ └─╴value: 0.0\n",
" └─╴feat: 3 <= 3.17, samples: 4853\n",
" ├─feat: 0 <= 1.21, samples: 214\n",
" │ ├─feat: 4 <= 0.85, samples: 71\n",
" │ │ ├─feat: 0 <= 1.15, samples: 49\n",
" │ │ │ └─╴value: 0.0\n",
" │ │ │ └─╴feat: 3 <= 2.25, samples: 3\n",
" │ │ │ └─╴value: 0.0\n",
" │ │ │ └─╴value: 1.0\n",
" │ │ └─╴feat: 1 <= 1.16, samples: 22\n",
" │ │ ├─feat: 0 <= 0.95, samples: 17\n",
" │ │ │ └─╴value: 0.0\n",
" │ │ │ └─╴value: 1.0\n",
" │ │ └─╴value: 1.0\n",
" │ └─╴feat: 0 <= 2.15, samples: 143\n",
" │ ├─feat: 3 <= 2.68, samples: 43\n",
" │ │ ├─feat: 1 <= -1.04, samples: 20\n",
" │ │ │ └─╴value: 0.0\n",
" │ │ │ └─╴value: 1.0\n",
" │ │ └─╴value: 1.0\n",
" │ └─╴value: 1.0\n",
" └─╴feat: 0 <= 0.16, samples: 4639\n",
" ├─feat: 3 <= 3.46, samples: 51\n",
" │ ├─feat: 1 <= -0.86, samples: 4\n",
" │ │ └─╴value: 0.0\n",
" │ │ └─╴feat: 1 <= 1.28, samples: 3\n",
" │ │ └─╴value: 1.0\n",
" │ │ └─╴value: 0.0\n",
" │ └─╴value: 1.0\n",
" └─╴value: 1.0\n",
"\n",
"————————————————————— tree: 08/50 ——————————————————————\n",
"split: CART, impurity: Entropy, leaf: Mode, nodes: 51\n",
"maxDepth: 7, reached depth: 7, minSamplesSplit: 2\n",
"························································\n",
"╴feat: 3 <= 2.20, samples: 9600\n",
" ├─feat: 3 <= 1.99, samples: 4747\n",
" │ ├─feat: 0 <= 1.43, samples: 4694\n",
" │ │ └─╴value: 0.0\n",
" │ │ └─╴feat: 3 <= 1.38, samples: 361\n",
" │ │ ├─feat: 4 <= 1.69, samples: 341\n",
" │ │ │ └─╴value: 0.0\n",
" │ │ │ └─╴feat: 2 <= 0.64, samples: 15\n",
" │ │ │ └─╴value: 0.0\n",
" │ │ │ └─╴value: 1.0\n",
" │ │ └─╴feat: 0 <= 1.90, samples: 20\n",
" │ │ └─╴value: 0.0\n",
" │ │ └─╴feat: 4 <= -0.37, samples: 9\n",
" │ │ └─╴value: 0.0\n",
" │ │ └─╴value: 1.0\n",
" │ └─╴feat: 0 <= 1.10, samples: 53\n",
" │ └─╴value: 0.0\n",
" │ └─╴feat: 3 <= 2.05, samples: 14\n",
" │ └─╴value: 0.0\n",
" │ └─╴feat: 2 <= 1.67, samples: 10\n",
" │ └─╴value: 1.0\n",
" │ └─╴value: 0.0\n",
" └─╴feat: 3 <= 3.17, samples: 4853\n",
" ├─feat: 0 <= 1.21, samples: 214\n",
" │ ├─feat: 4 <= 0.85, samples: 71\n",
" │ │ ├─feat: 0 <= 1.15, samples: 49\n",
" │ │ │ └─╴value: 0.0\n",
" │ │ │ └─╴feat: 3 <= 2.25, samples: 3\n",
" │ │ │ └─╴value: 0.0\n",
" │ │ │ └─╴value: 1.0\n",
" │ │ └─╴feat: 1 <= 1.16, samples: 22\n",
" │ │ ├─feat: 0 <= 0.95, samples: 17\n",
" │ │ │ └─╴value: 0.0\n",
" │ │ │ └─╴value: 1.0\n",
" │ │ └─╴value: 1.0\n",
" │ └─╴feat: 0 <= 2.15, samples: 143\n",
" │ ├─feat: 3 <= 2.68, samples: 43\n",
" │ │ ├─feat: 1 <= -1.04, samples: 20\n",
" │ │ │ └─╴value: 0.0\n",
" │ │ │ └─╴value: 1.0\n",
" │ │ └─╴value: 1.0\n",
" │ └─╴value: 1.0\n",
" └─╴feat: 0 <= 0.16, samples: 4639\n",
" ├─feat: 3 <= 3.46, samples: 51\n",
" │ ├─feat: 0 <= -0.50, samples: 4\n",
" │ │ └─╴value: 1.0\n",
" │ │ └─╴feat: 2 <= -0.75, samples: 3\n",
" │ │ └─╴value: 0.0\n",
" │ │ └─╴value: 0.0\n",
" │ └─╴value: 1.0\n",
" └─╴value: 1.0\n",
"\n",
"————————————————————— tree: 09/50 ——————————————————————\n",
"split: CART, impurity: Entropy, leaf: Mode, nodes: 51\n",
"maxDepth: 7, reached depth: 7, minSamplesSplit: 2\n",
"························································\n",
"╴feat: 3 <= 2.20, samples: 9600\n",
" ├─feat: 3 <= 1.99, samples: 4747\n",
" │ ├─feat: 0 <= 1.43, samples: 4694\n",
" │ │ └─╴value: 0.0\n",
" │ │ └─╴feat: 3 <= 1.38, samples: 361\n",
" │ │ ├─feat: 4 <= 1.69, samples: 341\n",
" │ │ │ └─╴value: 0.0\n",
" │ │ │ └─╴feat: 2 <= 0.64, samples: 15\n",
" │ │ │ └─╴value: 0.0\n",
" │ │ │ └─╴value: 1.0\n",
" │ │ └─╴feat: 0 <= 1.90, samples: 20\n",
" │ │ └─╴value: 0.0\n",
" │ │ └─╴feat: 4 <= -0.37, samples: 9\n",
" │ │ └─╴value: 0.0\n",
" │ │ └─╴value: 1.0\n",
" │ └─╴feat: 0 <= 1.10, samples: 53\n",
" │ └─╴value: 0.0\n",
" │ └─╴feat: 3 <= 2.05, samples: 14\n",
" │ └─╴value: 0.0\n",
" │ └─╴feat: 2 <= 1.67, samples: 10\n",
" │ └─╴value: 1.0\n",
" │ └─╴value: 0.0\n",
" └─╴feat: 3 <= 3.17, samples: 4853\n",
" ├─feat: 0 <= 1.21, samples: 214\n",
" │ ├─feat: 4 <= 0.85, samples: 71\n",
" │ │ ├─feat: 0 <= 1.15, samples: 49\n",
" │ │ │ └─╴value: 0.0\n",
" │ │ │ └─╴feat: 1 <= -0.70, samples: 3\n",
" │ │ │ └─╴value: 1.0\n",
" │ │ │ └─╴value: 0.0\n",
" │ │ └─╴feat: 1 <= 1.16, samples: 22\n",
" │ │ ├─feat: 0 <= 0.95, samples: 17\n",
" │ │ │ └─╴value: 0.0\n",
" │ │ │ └─╴value: 1.0\n",
" │ │ └─╴value: 1.0\n",
" │ └─╴feat: 0 <= 2.15, samples: 143\n",
" │ ├─feat: 3 <= 2.68, samples: 43\n",
" │ │ ├─feat: 1 <= -1.04, samples: 20\n",
" │ │ │ └─╴value: 0.0\n",
" │ │ │ └─╴value: 1.0\n",
" │ │ └─╴value: 1.0\n",
" │ └─╴value: 1.0\n",
" └─╴feat: 0 <= 0.16, samples: 4639\n",
" ├─feat: 3 <= 3.46, samples: 51\n",
" │ ├─feat: 0 <= -0.50, samples: 4\n",
" │ │ └─╴value: 1.0\n",
" │ │ └─╴feat: 0 <= -0.33, samples: 3\n",
" │ │ └─╴value: 0.0\n",
" │ │ └─╴value: 0.0\n",
" │ └─╴value: 1.0\n",
" └─╴value: 1.0\n",
"\n",
"————————————————————— tree: 10/50 ——————————————————————\n",
"split: CART, impurity: Entropy, leaf: Mode, nodes: 51\n",
"maxDepth: 7, reached depth: 7, minSamplesSplit: 2\n",
"························································\n",
"╴feat: 3 <= 2.20, samples: 9600\n",
" ├─feat: 3 <= 1.99, samples: 4747\n",
" │ ├─feat: 0 <= 1.43, samples: 4694\n",
" │ │ └─╴value: 0.0\n",
" │ │ └─╴feat: 3 <= 1.38, samples: 361\n",
" │ │ ├─feat: 4 <= 1.69, samples: 341\n",
" │ │ │ └─╴value: 0.0\n",
" │ │ │ └─╴feat: 2 <= 0.64, samples: 15\n",
" │ │ │ └─╴value: 0.0\n",
" │ │ │ └─╴value: 1.0\n",
" │ │ └─╴feat: 0 <= 1.90, samples: 20\n",
" │ │ └─╴value: 0.0\n",
" │ │ └─╴feat: 4 <= -0.37, samples: 9\n",
" │ │ └─╴value: 0.0\n",
" │ │ └─╴value: 1.0\n",
" │ └─╴feat: 0 <= 1.10, samples: 53\n",
" │ └─╴value: 0.0\n",
" │ └─╴feat: 3 <= 2.05, samples: 14\n",
" │ └─╴value: 0.0\n",
" │ └─╴feat: 2 <= 1.67, samples: 10\n",
" │ └─╴value: 1.0\n",
" │ └─╴value: 0.0\n",
" └─╴feat: 3 <= 3.17, samples: 4853\n",
" ├─feat: 0 <= 1.21, samples: 214\n",
" │ ├─feat: 4 <= 0.85, samples: 71\n",
" │ │ ├─feat: 0 <= 1.15, samples: 49\n",
" │ │ │ └─╴value: 0.0\n",
" │ │ │ └─╴feat: 2 <= 0.85, samples: 3\n",
" │ │ │ └─╴value: 0.0\n",
" │ │ │ └─╴value: 1.0\n",
" │ │ └─╴feat: 1 <= 1.16, samples: 22\n",
" │ │ ├─feat: 0 <= 0.95, samples: 17\n",
" │ │ │ └─╴value: 0.0\n",
" │ │ │ └─╴value: 1.0\n",
" │ │ └─╴value: 1.0\n",
" │ └─╴feat: 0 <= 2.15, samples: 143\n",
" │ ├─feat: 3 <= 2.68, samples: 43\n",
" │ │ ├─feat: 1 <= -1.04, samples: 20\n",
" │ │ │ └─╴value: 0.0\n",
" │ │ │ └─╴value: 1.0\n",
" │ │ └─╴value: 1.0\n",
" │ └─╴value: 1.0\n",
" └─╴feat: 0 <= 0.16, samples: 4639\n",
" ├─feat: 3 <= 3.46, samples: 51\n",
" │ ├─feat: 3 <= 3.32, samples: 4\n",
" │ │ └─╴value: 0.0\n",
" │ │ └─╴feat: 3 <= 3.42, samples: 3\n",
" │ │ └─╴value: 1.0\n",
" │ │ └─╴value: 0.0\n",
" │ └─╴value: 1.0\n",
" └─╴value: 1.0\n",
"\n",
"————————————————————— tree: 11/50 ——————————————————————\n",
"split: CART, impurity: Entropy, leaf: Mode, nodes: 51\n",
"maxDepth: 7, reached depth: 7, minSamplesSplit: 2\n",
"························································\n",
"╴feat: 3 <= 2.20, samples: 9600\n",
" ├─feat: 3 <= 1.99, samples: 4747\n",
" │ ├─feat: 0 <= 1.43, samples: 4694\n",
" │ │ └─╴value: 0.0\n",
" │ │ └─╴feat: 3 <= 1.38, samples: 361\n",
" │ │ ├─feat: 4 <= 1.69, samples: 341\n",
" │ │ │ └─╴value: 0.0\n",
" │ │ │ └─╴feat: 2 <= 0.64, samples: 15\n",
" │ │ │ └─╴value: 0.0\n",
" │ │ │ └─╴value: 1.0\n",
" │ │ └─╴feat: 0 <= 1.90, samples: 20\n",
" │ │ └─╴value: 0.0\n",
" │ │ └─╴feat: 4 <= -0.37, samples: 9\n",
" │ │ └─╴value: 0.0\n",
" │ │ └─╴value: 1.0\n",
" │ └─╴feat: 0 <= 1.10, samples: 53\n",
" │ └─╴value: 0.0\n",
" │ └─╴feat: 3 <= 2.05, samples: 14\n",
" │ └─╴value: 0.0\n",
" │ └─╴feat: 2 <= 1.67, samples: 10\n",
" │ └─╴value: 1.0\n",
" │ └─╴value: 0.0\n",
" └─╴feat: 3 <= 3.17, samples: 4853\n",
" ├─feat: 0 <= 1.21, samples: 214\n",
" │ ├─feat: 4 <= 0.85, samples: 71\n",
" │ │ ├─feat: 0 <= 1.15, samples: 49\n",
" │ │ │ └─╴value: 0.0\n",
" │ │ │ └─╴feat: 2 <= 0.85, samples: 3\n",
" │ │ │ └─╴value: 0.0\n",
" │ │ │ └─╴value: 1.0\n",
" │ │ └─╴feat: 1 <= 1.16, samples: 22\n",
" │ │ ├─feat: 0 <= 0.95, samples: 17\n",
" │ │ │ └─╴value: 0.0\n",
" │ │ │ └─╴value: 1.0\n",
" │ │ └─╴value: 1.0\n",
" │ └─╴feat: 0 <= 2.15, samples: 143\n",
" │ ├─feat: 3 <= 2.68, samples: 43\n",
" │ │ ├─feat: 1 <= -1.04, samples: 20\n",
" │ │ │ └─╴value: 0.0\n",
" │ │ │ └─╴value: 1.0\n",
" │ │ └─╴value: 1.0\n",
" │ └─╴value: 1.0\n",
" └─╴feat: 0 <= 0.16, samples: 4639\n",
" ├─feat: 3 <= 3.46, samples: 51\n",
" │ ├─feat: 3 <= 3.32, samples: 4\n",
" │ │ └─╴value: 0.0\n",
" │ │ └─╴feat: 1 <= -0.87, samples: 3\n",
" │ │ └─╴value: 0.0\n",
" │ │ └─╴value: 1.0\n",
" │ └─╴value: 1.0\n",
" └─╴value: 1.0\n",
"\n",
"————————————————————— tree: 12/50 ——————————————————————\n",
"split: CART, impurity: Entropy, leaf: Mode, nodes: 51\n",
"maxDepth: 7, reached depth: 7, minSamplesSplit: 2\n",
"························································\n",
"╴feat: 3 <= 2.20, samples: 9600\n",
" ├─feat: 3 <= 1.99, samples: 4747\n",
" │ ├─feat: 0 <= 1.43, samples: 4694\n",
" │ │ └─╴value: 0.0\n",
" │ │ └─╴feat: 3 <= 1.38, samples: 361\n",
" │ │ ├─feat: 4 <= 1.69, samples: 341\n",
" │ │ │ └─╴value: 0.0\n",
" │ │ │ └─╴feat: 2 <= 0.64, samples: 15\n",
" │ │ │ └─╴value: 0.0\n",
" │ │ │ └─╴value: 1.0\n",
" │ │ └─╴feat: 0 <= 1.90, samples: 20\n",
" │ │ └─╴value: 0.0\n",
" │ │ └─╴feat: 4 <= -0.37, samples: 9\n",
" │ │ └─╴value: 0.0\n",
" │ │ └─╴value: 1.0\n",
" │ └─╴feat: 0 <= 1.10, samples: 53\n",
" │ └─╴value: 0.0\n",
" │ └─╴feat: 3 <= 2.05, samples: 14\n",
" │ └─╴value: 0.0\n",
" │ └─╴feat: 2 <= 1.67, samples: 10\n",
" │ └─╴value: 1.0\n",
" │ └─╴value: 0.0\n",
" └─╴feat: 3 <= 3.17, samples: 4853\n",
" ├─feat: 0 <= 1.21, samples: 214\n",
" │ ├─feat: 4 <= 0.85, samples: 71\n",
" │ │ ├─feat: 0 <= 1.15, samples: 49\n",
" │ │ │ └─╴value: 0.0\n",
" │ │ │ └─╴feat: 3 <= 2.25, samples: 3\n",
" │ │ │ └─╴value: 0.0\n",
" │ │ │ └─╴value: 1.0\n",
" │ │ └─╴feat: 1 <= 1.16, samples: 22\n",
" │ │ ├─feat: 0 <= 0.95, samples: 17\n",
" │ │ │ └─╴value: 0.0\n",
" │ │ │ └─╴value: 1.0\n",
" │ │ └─╴value: 1.0\n",
" │ └─╴feat: 0 <= 2.15, samples: 143\n",
" │ ├─feat: 3 <= 2.68, samples: 43\n",
" │ │ ├─feat: 1 <= -1.04, samples: 20\n",
" │ │ │ └─╴value: 0.0\n",
" │ │ │ └─╴value: 1.0\n",
" │ │ └─╴value: 1.0\n",
" │ └─╴value: 1.0\n",
" └─╴feat: 0 <= 0.16, samples: 4639\n",
" ├─feat: 3 <= 3.46, samples: 51\n",
" │ ├─feat: 2 <= -0.77, samples: 4\n",
" │ │ └─╴value: 0.0\n",
" │ │ └─╴feat: 2 <= 0.21, samples: 3\n",
" │ │ └─╴value: 1.0\n",
" │ │ └─╴value: 0.0\n",
" │ └─╴value: 1.0\n",
" └─╴value: 1.0\n",
"\n",
"————————————————————— tree: 13/50 ——————————————————————\n",
"split: CART, impurity: Entropy, leaf: Mode, nodes: 51\n",
"maxDepth: 7, reached depth: 7, minSamplesSplit: 2\n",
"························································\n",
"╴feat: 3 <= 2.20, samples: 9600\n",
" ├─feat: 3 <= 1.99, samples: 4747\n",
" │ ├─feat: 0 <= 1.43, samples: 4694\n",
" │ │ └─╴value: 0.0\n",
" │ │ └─╴feat: 3 <= 1.38, samples: 361\n",
" │ │ ├─feat: 4 <= 1.69, samples: 341\n",
" │ │ │ └─╴value: 0.0\n",
" │ │ │ └─╴feat: 2 <= 0.64, samples: 15\n",
" │ │ │ └─╴value: 0.0\n",
" │ │ │ └─╴value: 1.0\n",
" │ │ └─╴feat: 0 <= 1.90, samples: 20\n",
" │ │ └─╴value: 0.0\n",
" │ │ └─╴feat: 4 <= -0.37, samples: 9\n",
" │ │ └─╴value: 0.0\n",
" │ │ └─╴value: 1.0\n",
" │ └─╴feat: 0 <= 1.10, samples: 53\n",
" │ └─╴value: 0.0\n",
" │ └─╴feat: 3 <= 2.05, samples: 14\n",
" │ └─╴value: 0.0\n",
" │ └─╴feat: 2 <= 1.67, samples: 10\n",
" │ └─╴value: 1.0\n",
" │ └─╴value: 0.0\n",
" └─╴feat: 3 <= 3.17, samples: 4853\n",
" ├─feat: 0 <= 1.21, samples: 214\n",
" │ ├─feat: 4 <= 0.85, samples: 71\n",
" │ │ ├─feat: 0 <= 1.15, samples: 49\n",
" │ │ │ └─╴value: 0.0\n",
" │ │ │ └─╴feat: 1 <= -0.70, samples: 3\n",
" │ │ │ └─╴value: 1.0\n",
" │ │ │ └─╴value: 0.0\n",
" │ │ └─╴feat: 1 <= 1.16, samples: 22\n",
" │ │ ├─feat: 3 <= 2.86, samples: 17\n",
" │ │ │ └─╴value: 0.0\n",
" │ │ │ └─╴value: 1.0\n",
" │ │ └─╴value: 1.0\n",
" │ └─╴feat: 0 <= 2.15, samples: 143\n",
" │ ├─feat: 3 <= 2.68, samples: 43\n",
" │ │ ├─feat: 1 <= -1.04, samples: 20\n",
" │ │ │ └─╴value: 0.0\n",
" │ │ │ └─╴value: 1.0\n",
" │ │ └─╴value: 1.0\n",
" │ └─╴value: 1.0\n",
" └─╴feat: 0 <= 0.16, samples: 4639\n",
" ├─feat: 3 <= 3.46, samples: 51\n",
" │ ├─feat: 1 <= -0.86, samples: 4\n",
" │ │ └─╴value: 0.0\n",
" │ │ └─╴feat: 3 <= 3.32, samples: 3\n",
" │ │ └─╴value: 0.0\n",
" │ │ └─╴value: 1.0\n",
" │ └─╴value: 1.0\n",
" └─╴value: 1.0\n",
"\n",
"————————————————————— tree: 14/50 ——————————————————————\n",
"split: CART, impurity: Entropy, leaf: Mode, nodes: 51\n",
"maxDepth: 7, reached depth: 7, minSamplesSplit: 2\n",
"························································\n",
"╴feat: 3 <= 2.20, samples: 9600\n",
" ├─feat: 3 <= 1.99, samples: 4747\n",
" │ ├─feat: 0 <= 1.43, samples: 4694\n",
" │ │ └─╴value: 0.0\n",
" │ │ └─╴feat: 3 <= 1.38, samples: 361\n",
" │ │ ├─feat: 4 <= 1.69, samples: 341\n",
" │ │ │ └─╴value: 0.0\n",
" │ │ │ └─╴feat: 2 <= 0.64, samples: 15\n",
" │ │ │ └─╴value: 0.0\n",
" │ │ │ └─╴value: 1.0\n",
" │ │ └─╴feat: 0 <= 1.90, samples: 20\n",
" │ │ └─╴value: 0.0\n",
" │ │ └─╴feat: 4 <= -0.37, samples: 9\n",
" │ │ └─╴value: 0.0\n",
" │ │ └─╴value: 1.0\n",
" │ └─╴feat: 0 <= 1.10, samples: 53\n",
" │ └─╴value: 0.0\n",
" │ └─╴feat: 3 <= 2.05, samples: 14\n",
" │ └─╴value: 0.0\n",
" │ └─╴feat: 2 <= 1.67, samples: 10\n",
" │ └─╴value: 1.0\n",
" │ └─╴value: 0.0\n",
" └─╴feat: 3 <= 3.17, samples: 4853\n",
" ├─feat: 0 <= 1.21, samples: 214\n",
" │ ├─feat: 4 <= 0.85, samples: 71\n",
" │ │ ├─feat: 0 <= 1.15, samples: 49\n",
" │ │ │ └─╴value: 0.0\n",
" │ │ │ └─╴feat: 3 <= 2.25, samples: 3\n",
" │ │ │ └─╴value: 0.0\n",
" │ │ │ └─╴value: 1.0\n",
" │ │ └─╴feat: 1 <= 1.16, samples: 22\n",
" │ │ ├─feat: 0 <= 0.95, samples: 17\n",
" │ │ │ └─╴value: 0.0\n",
" │ │ │ └─╴value: 1.0\n",
" │ │ └─╴value: 1.0\n",
" │ └─╴feat: 0 <= 2.15, samples: 143\n",
" │ ├─feat: 3 <= 2.68, samples: 43\n",
" │ │ ├─feat: 1 <= -1.04, samples: 20\n",
" │ │ │ └─╴value: 0.0\n",
" │ │ │ └─╴value: 1.0\n",
" │ │ └─╴value: 1.0\n",
" │ └─╴value: 1.0\n",
" └─╴feat: 0 <= 0.16, samples: 4639\n",
" ├─feat: 3 <= 3.46, samples: 51\n",
" │ ├─feat: 0 <= -0.50, samples: 4\n",
" │ │ └─╴value: 1.0\n",
" │ │ └─╴feat: 0 <= -0.33, samples: 3\n",
" │ │ └─╴value: 0.0\n",
" │ │ └─╴value: 0.0\n",
" │ └─╴value: 1.0\n",
" └─╴value: 1.0\n",
"\n",
"————————————————————— tree: 15/50 ——————————————————————\n",
"split: CART, impurity: Entropy, leaf: Mode, nodes: 51\n",
"maxDepth: 7, reached depth: 7, minSamplesSplit: 2\n",
"························································\n",
"╴feat: 3 <= 2.20, samples: 9600\n",
" ├─feat: 3 <= 1.99, samples: 4747\n",
" │ ├─feat: 0 <= 1.43, samples: 4694\n",
" │ │ └─╴value: 0.0\n",
" │ │ └─╴feat: 3 <= 1.38, samples: 361\n",
" │ │ ├─feat: 4 <= 1.69, samples: 341\n",
" │ │ │ └─╴value: 0.0\n",
" │ │ │ └─╴feat: 2 <= 0.64, samples: 15\n",
" │ │ │ └─╴value: 0.0\n",