Run_ensemble_report.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "from filewise_ensemble import file_wise_ensemble"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "*********** Datasets/autoencoder_dataset ***********\n",
      "Prediction scores of each tree corresponding to each point\n",
      "{'Fp1': 1.0, 'Fp2': 0.4185185185185185, 'F3': 0.4444444444444444, 'F4': 0.3925925925925926, 'C3': 0.4648148148148148, 'C4': 0.45925925925925926, 'P3': 0.5351851851851852, 'P4': 0.48148148148148145, 'O1': 0.4981481481481482, 'O2': 0.45925925925925926, 'A1': 0.4351851851851852, 'A2': 0.4074074074074074, 'F7': 0.39814814814814814, 'F8': 0.4388888888888889, 'T3': 0.39444444444444443, 'T4': 0.35, 'T5': 0.5277777777777778, 'T6': 0.4074074074074074, 'Fz': 0.38333333333333336, 'Cz': 0.4444444444444444, 'Pz': 0.4388888888888889}\n",
      "maximum accuracy of data point: Fp1\n",
      "\n",
      " Final classification result after voting \n",
      "\n",
      "              precision    recall  f1-score   support\n",
      "\n",
      "           1       0.67      0.75      0.71       171\n",
      "           2       0.80      0.71      0.75       214\n",
      "           3       0.77      0.81      0.79       155\n",
      "\n",
      "    accuracy                           0.75       540\n",
      "   macro avg       0.75      0.75      0.75       540\n",
      "weighted avg       0.75      0.75      0.75       540\n",
      "\n",
      "*********** Datasets/CLA-SubjectJ-170504-3St-LRHand-Inter ***********\n",
      "Prediction scores of each tree corresponding to each point\n",
      "{'Fp1': 1.0, 'Fp2': 0.5777777777777777, 'F3': 0.6944444444444444, 'F4': 0.6777777777777778, 'C3': 0.6833333333333333, 'C4': 0.5333333333333333, 'P3': 0.7666666666666667, 'P4': 0.6722222222222223, 'O1': 0.7611111111111111, 'O2': 0.7277777777777777, 'A1': 0.6166666666666667, 'A2': 0.7, 'F7': 0.6388888888888888, 'F8': 0.75, 'T3': 0.6055555555555555, 'T4': 0.7611111111111111, 'T5': 0.6777777777777778, 'T6': 0.7888888888888889, 'Fz': 0.7, 'Cz': 0.7222222222222222, 'Pz': 0.6222222222222222}\n",
      "maximum accuracy of data point: Fp1\n",
      "\n",
      " Final classification result after voting \n",
      "\n",
      "              precision    recall  f1-score   support\n",
      "\n",
      "           1       0.98      1.00      0.99        51\n",
      "           2       1.00      0.95      0.97        76\n",
      "           3       0.95      1.00      0.97        53\n",
      "\n",
      "    accuracy                           0.98       180\n",
      "   macro avg       0.98      0.98      0.98       180\n",
      "weighted avg       0.98      0.98      0.98       180\n",
      "\n",
      "*********** Datasets/CLA-SubjectJ-170508-3St-LRHand-Inter ***********\n",
      "Prediction scores of each tree corresponding to each point\n",
      "{'Fp1': 1.0, 'Fp2': 0.7166666666666667, 'F3': 0.6277777777777778, 'F4': 0.6888888888888889, 'C3': 0.6555555555555556, 'C4': 0.6277777777777778, 'P3': 0.6166666666666667, 'P4': 0.6055555555555555, 'O1': 0.7222222222222222, 'O2': 0.5444444444444444, 'A1': 0.7888888888888889, 'A2': 0.7444444444444445, 'F7': 0.6888888888888889, 'F8': 0.7111111111111111, 'T3': 0.7277777777777777, 'T4': 0.7944444444444444, 'T5': 0.7277777777777777, 'T6': 0.6666666666666666, 'Fz': 0.7333333333333333, 'Cz': 0.6777777777777778, 'Pz': 0.6333333333333333}\n",
      "maximum accuracy of data point: Fp1\n",
      "\n",
      " Final classification result after voting \n",
      "\n",
      "              precision    recall  f1-score   support\n",
      "\n",
      "           1       0.92      1.00      0.96        54\n",
      "           2       1.00      0.89      0.94        72\n",
      "           3       0.95      1.00      0.97        54\n",
      "\n",
      "    accuracy                           0.96       180\n",
      "   macro avg       0.95      0.96      0.96       180\n",
      "weighted avg       0.96      0.96      0.96       180\n",
      "\n",
      "*********** Datasets/CLA-SubjectJ-170510-3St-LRHand-Inter ***********\n",
      "Prediction scores of each tree corresponding to each point\n",
      "{'Fp1': 1.0, 'Fp2': 0.6888888888888889, 'F3': 0.5111111111111111, 'F4': 0.7111111111111111, 'C3': 0.6333333333333333, 'C4': 0.7166666666666667, 'P3': 0.5444444444444444, 'P4': 0.85, 'O1': 0.7055555555555556, 'O2': 0.6277777777777778, 'A1': 0.5833333333333334, 'A2': 0.5166666666666667, 'F7': 0.46111111111111114, 'F8': 0.65, 'T3': 0.5, 'T4': 0.6444444444444445, 'T5': 0.4666666666666667, 'T6': 0.5277777777777778, 'Fz': 0.7611111111111111, 'Cz': 0.8, 'Pz': 0.6722222222222223}\n",
      "maximum accuracy of data point: Fp1\n",
      "\n",
      " Final classification result after voting \n",
      "\n",
      "              precision    recall  f1-score   support\n",
      "\n",
      "           1       0.97      1.00      0.98        59\n",
      "           2       0.99      0.96      0.97        75\n",
      "           3       0.96      0.96      0.96        46\n",
      "\n",
      "    accuracy                           0.97       180\n",
      "   macro avg       0.97      0.97      0.97       180\n",
      "weighted avg       0.97      0.97      0.97       180\n",
      "\n"
     ]
    }
   ],
   "source": [
    "file_wise_ensemble()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "*********** Datasets/autoencoder_dataset ***********\n",
      "Prediction scores of each tree corresponding to each point\n",
      "{'Fp1': 0.9981481481481481, 'Fp2': 0.4148148148148148, 'F3': 0.4166666666666667, 'F4': 0.362962962962963, 'C3': 0.4759259259259259, 'C4': 0.43703703703703706, 'P3': 0.5092592592592593, 'P4': 0.48333333333333334, 'O1': 0.5074074074074074, 'O2': 0.42592592592592593, 'A1': 0.362962962962963, 'A2': 0.4185185185185185, 'F7': 0.3888888888888889, 'F8': 0.46296296296296297, 'T3': 0.4203703703703704, 'T4': 0.3888888888888889, 'T5': 0.5185185185185185, 'T6': 0.42407407407407405, 'Fz': 0.40925925925925927, 'Cz': 0.4462962962962963, 'Pz': 0.4351851851851852}\n",
      "maximum accuracy of data point: Fp1\n",
      "\n",
      " Final classification result after voting \n",
      "\n",
      "              precision    recall  f1-score   support\n",
      "\n",
      "           1       0.41      0.41      0.41       160\n",
      "           2       0.53      0.53      0.53       204\n",
      "           3       0.51      0.52      0.52       176\n",
      "\n",
      "    accuracy                           0.49       540\n",
      "   macro avg       0.49      0.49      0.49       540\n",
      "weighted avg       0.49      0.49      0.49       540\n",
      "\n",
      "*********** Datasets/CLA-SubjectJ-170504-3St-LRHand-Inter ***********\n",
      "Prediction scores of each tree corresponding to each point\n",
      "{'Fp1': 1.0, 'Fp2': 0.6222222222222222, 'F3': 0.5888888888888889, 'F4': 0.6833333333333333, 'C3': 0.6777777777777778, 'C4': 0.5111111111111111, 'P3': 0.7722222222222223, 'P4': 0.7277777777777777, 'O1': 0.7055555555555556, 'O2': 0.7333333333333333, 'A1': 0.6333333333333333, 'A2': 0.6777777777777778, 'F7': 0.6333333333333333, 'F8': 0.6611111111111111, 'T3': 0.6833333333333333, 'T4': 0.7333333333333333, 'T5': 0.6777777777777778, 'T6': 0.7, 'Fz': 0.6111111111111112, 'Cz': 0.7555555555555555, 'Pz': 0.65}\n",
      "maximum accuracy of data point: Fp1\n",
      "\n",
      " Final classification result after voting \n",
      "\n",
      "              precision    recall  f1-score   support\n",
      "\n",
      "           1       0.92      0.64      0.76        84\n",
      "           2       0.81      0.76      0.79        55\n",
      "           3       0.51      0.85      0.64        41\n",
      "\n",
      "    accuracy                           0.73       180\n",
      "   macro avg       0.74      0.75      0.73       180\n",
      "weighted avg       0.79      0.73      0.74       180\n",
      "\n",
      "*********** Datasets/CLA-SubjectJ-170508-3St-LRHand-Inter ***********\n",
      "Prediction scores of each tree corresponding to each point\n",
      "{'Fp1': 1.0, 'Fp2': 0.6833333333333333, 'F3': 0.5777777777777777, 'F4': 0.7166666666666667, 'C3': 0.7, 'C4': 0.6833333333333333, 'P3': 0.5611111111111111, 'P4': 0.6611111111111111, 'O1': 0.6555555555555556, 'O2': 0.5277777777777778, 'A1': 0.7666666666666667, 'A2': 0.7277777777777777, 'F7': 0.7, 'F8': 0.75, 'T3': 0.7111111111111111, 'T4': 0.7055555555555556, 'T5': 0.6166666666666667, 'T6': 0.6277777777777778, 'Fz': 0.7111111111111111, 'Cz': 0.6777777777777778, 'Pz': 0.6388888888888888}\n",
      "maximum accuracy of data point: Fp1\n",
      "\n",
      " Final classification result after voting \n",
      "\n",
      "              precision    recall  f1-score   support\n",
      "\n",
      "           1       0.82      1.00      0.90        56\n",
      "           2       0.67      0.75      0.70        51\n",
      "           3       0.78      0.59      0.67        73\n",
      "\n",
      "    accuracy                           0.76       180\n",
      "   macro avg       0.76      0.78      0.76       180\n",
      "weighted avg       0.76      0.76      0.75       180\n",
      "\n",
      "*********** Datasets/CLA-SubjectJ-170510-3St-LRHand-Inter ***********\n",
      "Prediction scores of each tree corresponding to each point\n",
      "{'Fp1': 0.9944444444444445, 'Fp2': 0.6388888888888888, 'F3': 0.5444444444444444, 'F4': 0.7166666666666667, 'C3': 0.6222222222222222, 'C4': 0.7111111111111111, 'P3': 0.5666666666666667, 'P4': 0.8222222222222222, 'O1': 0.75, 'O2': 0.6833333333333333, 'A1': 0.5444444444444444, 'A2': 0.5388888888888889, 'F7': 0.4666666666666667, 'F8': 0.6111111111111112, 'T3': 0.5055555555555555, 'T4': 0.6277777777777778, 'T5': 0.5611111111111111, 'T6': 0.5833333333333334, 'Fz': 0.6944444444444444, 'Cz': 0.7444444444444445, 'Pz': 0.65}\n",
      "maximum accuracy of data point: Fp1\n",
      "\n",
      " Final classification result after voting \n",
      "\n",
      "              precision    recall  f1-score   support\n",
      "\n",
      "           1       0.95      0.84      0.89        64\n",
      "           2       0.75      0.85      0.79        59\n",
      "           3       0.79      0.77      0.78        57\n",
      "\n",
      "    accuracy                           0.82       180\n",
      "   macro avg       0.83      0.82      0.82       180\n",
      "weighted avg       0.83      0.82      0.82       180\n",
      "\n"
     ]
    }
   ],
   "source": [
    "list_area = ['F3,''F4','C3','C4','Cz']\n",
    "file_wise_ensemble(only_motor=True, list_area = list_area)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "*********** Datasets/autoencoder_dataset ***********\n",
      "Prediction scores of each tree corresponding to each point\n",
      "{'Fp1': 1.0, 'Fp2': 0.3611111111111111, 'F3': 0.4148148148148148, 'F4': 0.4166666666666667, 'C3': 0.40185185185185185, 'C4': 0.4462962962962963, 'P3': 0.512962962962963, 'P4': 0.4666666666666667, 'O1': 0.5018518518518519, 'O2': 0.4722222222222222, 'A1': 0.4185185185185185, 'A2': 0.3925925925925926, 'F7': 0.3925925925925926, 'F8': 0.43333333333333335, 'T3': 0.38333333333333336, 'T4': 0.37962962962962965, 'T5': 0.4981481481481482, 'T6': 0.42777777777777776, 'Fz': 0.40370370370370373, 'Cz': 0.42407407407407405, 'Pz': 0.3962962962962963}\n",
      "maximum accuracy of data point: Fp1\n",
      "\n",
      " Final classification result after voting \n",
      "\n",
      "              precision    recall  f1-score   support\n",
      "\n",
      "           1       0.40      0.52      0.45       141\n",
      "           2       0.67      0.51      0.58       236\n",
      "           3       0.52      0.56      0.54       163\n",
      "\n",
      "    accuracy                           0.53       540\n",
      "   macro avg       0.53      0.53      0.52       540\n",
      "weighted avg       0.55      0.53      0.53       540\n",
      "\n",
      "*********** Datasets/CLA-SubjectJ-170504-3St-LRHand-Inter ***********\n",
      "Prediction scores of each tree corresponding to each point\n",
      "{'Fp1': 1.0, 'Fp2': 0.6, 'F3': 0.6388888888888888, 'F4': 0.6833333333333333, 'C3': 0.7, 'C4': 0.5611111111111111, 'P3': 0.7777777777777778, 'P4': 0.6666666666666666, 'O1': 0.7611111111111111, 'O2': 0.6888888888888889, 'A1': 0.6166666666666667, 'A2': 0.6444444444444445, 'F7': 0.6555555555555556, 'F8': 0.7611111111111111, 'T3': 0.6333333333333333, 'T4': 0.7, 'T5': 0.6777777777777778, 'T6': 0.7555555555555555, 'Fz': 0.6722222222222223, 'Cz': 0.7277777777777777, 'Pz': 0.6111111111111112}\n",
      "maximum accuracy of data point: Fp1\n",
      "\n",
      " Final classification result after voting \n",
      "\n",
      "              precision    recall  f1-score   support\n",
      "\n",
      "           1       0.96      0.96      0.96        56\n",
      "           2       0.96      1.00      0.98        66\n",
      "           3       0.98      0.93      0.96        58\n",
      "\n",
      "    accuracy                           0.97       180\n",
      "   macro avg       0.97      0.97      0.97       180\n",
      "weighted avg       0.97      0.97      0.97       180\n",
      "\n",
      "*********** Datasets/CLA-SubjectJ-170508-3St-LRHand-Inter ***********\n",
      "Prediction scores of each tree corresponding to each point\n",
      "{'Fp1': 0.9944444444444445, 'Fp2': 0.7055555555555556, 'F3': 0.5777777777777777, 'F4': 0.7444444444444445, 'C3': 0.6388888888888888, 'C4': 0.6277777777777778, 'P3': 0.5555555555555556, 'P4': 0.6444444444444445, 'O1': 0.7444444444444445, 'O2': 0.5611111111111111, 'A1': 0.7666666666666667, 'A2': 0.75, 'F7': 0.7111111111111111, 'F8': 0.6611111111111111, 'T3': 0.7111111111111111, 'T4': 0.8111111111111111, 'T5': 0.6833333333333333, 'T6': 0.5722222222222222, 'Fz': 0.7222222222222222, 'Cz': 0.6111111111111112, 'Pz': 0.6388888888888888}\n",
      "maximum accuracy of data point: Fp1\n",
      "\n",
      " Final classification result after voting \n",
      "\n",
      "              precision    recall  f1-score   support\n",
      "\n",
      "           1       0.90      0.97      0.93        58\n",
      "           2       1.00      0.84      0.91        74\n",
      "           3       0.82      0.96      0.88        48\n",
      "\n",
      "    accuracy                           0.91       180\n",
      "   macro avg       0.91      0.92      0.91       180\n",
      "weighted avg       0.92      0.91      0.91       180\n",
      "\n",
      "*********** Datasets/CLA-SubjectJ-170510-3St-LRHand-Inter ***********\n",
      "Prediction scores of each tree corresponding to each point\n",
      "{'Fp1': 1.0, 'Fp2': 0.6611111111111111, 'F3': 0.5055555555555555, 'F4': 0.6888888888888889, 'C3': 0.6111111111111112, 'C4': 0.6388888888888888, 'P3': 0.6055555555555555, 'P4': 0.7555555555555555, 'O1': 0.7, 'O2': 0.7444444444444445, 'A1': 0.5, 'A2': 0.4888888888888889, 'F7': 0.45, 'F8': 0.6611111111111111, 'T3': 0.5277777777777778, 'T4': 0.6333333333333333, 'T5': 0.5166666666666667, 'T6': 0.55, 'Fz': 0.7222222222222222, 'Cz': 0.7944444444444444, 'Pz': 0.7111111111111111}\n",
      "maximum accuracy of data point: Fp1\n",
      "\n",
      " Final classification result after voting \n",
      "\n",
      "              precision    recall  f1-score   support\n",
      "\n",
      "           1       0.79      0.94      0.86        51\n",
      "           2       0.84      0.82      0.83        66\n",
      "           3       0.89      0.78      0.83        63\n",
      "\n",
      "    accuracy                           0.84       180\n",
      "   macro avg       0.84      0.85      0.84       180\n",
      "weighted avg       0.84      0.84      0.84       180\n",
      "\n"
     ]
    }
   ],
   "source": [
    "list_area = ['C3','C4','T4','Cz','P3','P4','O1','A1','T3']\n",
    "file_wise_ensemble(only_motor=True, list_area = list_area)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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