{ "cells": [ { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "%pip install awswrangler pycaret[full]\n", "%pip install xgboost" ] }, { "cell_type": "code", "execution_count": 2, "metadata": {}, "outputs": [], "source": [ "# import awswrangler as wr\n", "import pandas as pd\n", "import numpy as np\n", "# import boto3\n", "# from sagemaker import get_execution_role\n", "import datetime\n", "import string\n", "import random\n", "from pycaret.classification import *" ] }, { "cell_type": "code", "execution_count": 3, "metadata": {}, "outputs": [], "source": [ "data = pd.read_csv('data/data_feature_eng.csv')\n", "# print(data)" ] }, { "cell_type": "code", "execution_count": 4, "metadata": {}, "outputs": [ { "data": { "text/html": [ "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
 DescriptionValue
0session_id1504
1Targetlabel
2Target TypeBinary
3Label Encoded0.0: 0, 1.0: 1
4Original Data(64800, 13)
5Missing ValuesFalse
6Numeric Features10
7Categorical Features2
8Ordinal FeaturesFalse
9High Cardinality FeaturesFalse
10High Cardinality MethodNone
11Transformed Train Set(45359, 21)
12Transformed Test Set(19441, 21)
13Shuffle Train-TestTrue
14Stratify Train-TestFalse
15Fold GeneratorStratifiedKFold
16Fold Number10
17CPU Jobs-1
18Use GPUTrue
19Log ExperimentFalse
20Experiment Nameclf-default-name
21USIece6
22Imputation Typesimple
23Iterative Imputation IterationNone
24Numeric Imputermean
25Iterative Imputation Numeric ModelNone
26Categorical Imputerconstant
27Iterative Imputation Categorical ModelNone
28Unknown Categoricals Handlingleast_frequent
29NormalizeTrue
30Normalize Methodzscore
31TransformationFalse
32Transformation MethodNone
33PCAFalse
34PCA MethodNone
35PCA ComponentsNone
36Ignore Low VarianceFalse
37Combine Rare LevelsFalse
38Rare Level ThresholdNone
39Numeric BinningFalse
40Remove OutliersFalse
41Outliers ThresholdNone
42Remove MulticollinearityFalse
43Multicollinearity ThresholdNone
44Remove Perfect CollinearityTrue
45ClusteringFalse
46Clustering IterationNone
47Polynomial FeaturesFalse
48Polynomial DegreeNone
49Trignometry FeaturesFalse
50Polynomial ThresholdNone
51Group FeaturesFalse
52Feature SelectionFalse
53Feature Selection Methodclassic
54Features Selection ThresholdNone
55Feature InteractionFalse
56Feature RatioFalse
57Interaction ThresholdNone
58Fix ImbalanceFalse
59Fix Imbalance MethodSMOTE
\n" ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "m_setup = setup(data=data, target='label', normalize=True, \n", " feature_interaction=False, \n", " feature_ratio=False,\n", " trigonometry_features=False,\n", " use_gpu=True)" ] }, { "cell_type": "code", "execution_count": 4, "metadata": {}, "outputs": [ { "data": { "text/html": [ "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
 AccuracyAUCRecallPrec.F1KappaMCC
00.97750.99460.92990.92190.92590.91260.9126
10.97930.99490.93720.92640.93180.91960.9196
20.98260.99500.93440.94960.94200.93170.9318
30.97950.99570.93000.93410.93210.92000.9200
40.98040.99570.94310.92830.93560.92410.9241
50.97730.99510.93000.92060.92530.91190.9119
60.98170.99750.93000.94800.93890.92820.9282
70.98100.99460.93590.93860.93720.92610.9261
80.98020.99580.93000.93820.93410.92240.9224
90.98020.99620.92550.94210.93370.92210.9221
Mean0.98000.99550.93260.93480.93370.92190.9219
SD0.00160.00080.00480.00980.00500.00590.0059
\n" ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# max_depth = 트리 최대 깊이\n", "# max_leaves = 트리 최대 리프\n", "# subsample = row sampling\n", "# colsample_bytree = column sampling 각 이터레이션에 사용되는 칼럼의 비율\n", "# 일반적으로 row sampling 보다는 column sampling이 모형성능과 학습시간에 더 큰 영향을 준다\n", "# xgboost = create_model('xgboost', max_depth=16, max_leaves=255)\n", "# xgboost = create_model('xgboost')\n", "xgboost = create_model('xgboost', max_depth=8, max_leaves=255)\n", "# best_model = compare_models(n_select=6)" ] }, { "cell_type": "code", "execution_count": 5, "metadata": {}, "outputs": [ { "data": { "text/html": [ "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
 AccuracyAUCRecallPrec.F1KappaMCC
00.97570.99490.91970.91970.91970.90540.9054
10.97860.99570.93580.92360.92970.91710.9171
20.98260.99600.94020.94440.94230.93200.9320
30.98130.99640.93880.93740.93810.92710.9271
40.98370.99660.94900.94350.94620.93660.9366
50.97820.99550.92710.92850.92780.91490.9149
60.98320.99800.93730.95120.94420.93430.9344
70.98040.99530.94020.93070.93550.92390.9239
80.98130.99560.93730.93870.93800.92700.9270
90.98060.99670.92410.94620.93500.92360.9237
Mean0.98060.99610.93500.93640.93560.92420.9242
SD0.00230.00080.00830.00990.00770.00910.0091
\n" ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# max leaves -> 2**(n-1), n = max_depth\n", "params = {'max_depth': [128, 64, 32],\n", " 'max_leaves': [256, 1024, 4096], \n", " 'colsample_bytree':[0.2, 0.4, 0.6, 0.8, 1.0],\n", " 'learning_rate':[0.05, 0.005]\n", " }#range(14,17)}\n", "# tuned_xgboost = tune_model(xgboost, optimize='F1', custom_grid=params)\n", "tuned_xgboost = tune_model(xgboost, optimize='Accuracy', custom_grid=params, tuner_verbose=3)\n", "# tuned_xgboost = tune_model(xgboost, optimize='Kappa')" ] }, { "cell_type": "code", "execution_count": 6, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "XGBClassifier(base_score=0.5, booster='gbtree', colsample_bylevel=1,\n", " colsample_bynode=1, colsample_bytree=0.8,\n", " enable_categorical=False, gamma=0, gpu_id=0, importance_type=None,\n", " interaction_constraints='', learning_rate=0.05, max_delta_step=0,\n", " max_depth=32, max_leaves=1024, min_child_weight=1, missing=nan,\n", " monotone_constraints='()', n_estimators=100, n_jobs=-1,\n", " num_parallel_tree=1, objective='binary:logistic',\n", " predictor='auto', random_state=6868, reg_alpha=0, reg_lambda=1,\n", " scale_pos_weight=1, subsample=1, tree_method='gpu_hist',\n", " use_label_encoder=True, validate_parameters=1, ...)" ] }, "execution_count": 6, "metadata": {}, "output_type": "execute_result" } ], "source": [ "tuned_xgboost" ] }, { "cell_type": "code", "execution_count": 8, "metadata": {}, "outputs": [ { "data": { "image/png": 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