質問編集履歴

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ソースの追加

2020/04/20 06:53

投稿

Rondon7251
Rondon7251

スコア89

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  何かわかる方いましたら教えてください。
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+ ```python
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+ import pandas as pd
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+ from sklearn.model_selection import train_test_split
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+ from sklearn.svm import SVC
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+ from sklearn.metrics import accuracy_score
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+ from sklearn.metrics import confusion_matrix
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+ from sklearn.metrics import f1_score
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+ # データの読み込み --- (*1)
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+ analysisresults_data = pd.read_csv("analysis_resultstableFAB.csv",encoding="utf-8")
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+ # データをラベルと入力データに分離する --- (*2)
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+ y = analysisresults_data.loc[:,"analysis_result"]
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+ x = analysisresults_data.loc[:,["signatures_id","hit_count"]]
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+ # 学習用とテスト用に分離する --- (*3)
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+ x_train, x_test, y_train, y_test = train_test_split(x, y, test_size = 0.2, train_size = 0.8, shuffle = True, random_state=0)
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+ # 学習する --- (*4)
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+ clf = SVC()
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+ clf.fit(x_train, y_train)
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+ # 評価する --- (*5)
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+ y_pred = clf.predict(x_test)
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+ print("正解率 = " , accuracy_score(y_test, y_pred))
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+ tp, fn, fp, tn = confusion_matrix(y_test, y_pred).ravel()
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+ print("TP,FN,FP,TN = ",tp,fn,fp,tn)
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+ FPR = fp/(fp+tn)
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+ print("偽陽性率 = ",FPR)
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+ print("F値 = " , f1_score(y_test, y_pred))
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+ ```