From 457248b9fa059cb4be1482a26cf90c7b7c443c86 Mon Sep 17 00:00:00 2001 From: s464931 Date: Wed, 18 May 2022 01:10:31 +0200 Subject: [PATCH] =?UTF-8?q?Drzewo=20decyzyjne=20-=20uzupe=C5=82nienie?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit --- dataset.csv | 238 +++++++++++++++++++++++++++++++++++++++++++--------- drzewo.png | Bin 0 -> 160421 bytes rescue.py | 17 ++-- 3 files changed, 211 insertions(+), 44 deletions(-) create mode 100644 drzewo.png diff --git a/dataset.csv b/dataset.csv index 6108118..181b121 100644 --- a/dataset.csv +++ b/dataset.csv @@ -1,39 +1,201 @@ plec;wiek;czas_w_pom;temp_w_pom;poziom_kurzu;poziom_oswietlenia;niebezp_towary;decyzja -2;1;3;0;2;1;0;1 -2;1;3;0;1;1;1;1 -2;1;3;0;1;1;0;0 -2;1;3;0;1;2;0;0 -1;1;3;0;1;1;0;1 -2;1;2;0;2;1;1;1 -2;1;2;0;2;2;1;1 -2;1;2;0;1;1;1;0 -2;1;2;0;1;2;1;0 -1;1;2;0;1;1;1;1 -1;1;2;0;2;1;0;0 -2;1;3;1;2;1;1;1 -2;1;3;1;2;2;1;1 -2;1;3;1;1;1;1;0 -1;1;3;1;1;1;1;1 -1;1;3;1;1;2;1;1 -1;1;3;1;2;1;0;0 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krata import * +from sklearn import metrics, tree def drzewo_decyzyjne(): columns = ['plec', 'wiek', 'czas_w_pom', 'temp_w_pom', 'poziom_kurzu', 'poziom_oswietlenia', 'niebezp_towary', 'decyzja'] df = pd.read_csv("dataset.csv", header=0, sep=";", names=columns) - x = df[['plec', 'wiek', 'czas_w_pom', 'temp_w_pom', 'poziom_kurzu', 'poziom_oswietlenia', 'niebezp_towary']] + kolumny_x=['plec', 'wiek', 'czas_w_pom', 'temp_w_pom', 'poziom_kurzu', 'poziom_oswietlenia', 'niebezp_towary'] + x = df[kolumny_x] y = df.decyzja #df.info() #X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.3) clf = DecisionTreeClassifier() clf = clf.fit(x, y) # print("Dokładność: ", metrics.accuracy_score(y_test, y_pred)) + + dot_data = tree.export_graphviz(clf, out_file=None, feature_names=kolumny_x, class_names=['0', '1']) + graph = pydotplus.graph_from_dot_data(dot_data) + graph.write_png('drzewo.png') + return clf def decyzja_osoba(osoba: PoleKraty, clf: DecisionTreeClassifier): z=[] z.extend(random.choices([1,2], weights=[1,2], k=1)) #1 kobieta, 2 mężczyzna - z.extend(random.choices([1, 2], weights=[4,1], k=1)) # 1 dorosły, 2 osoba starsza - z.extend(random.choices([1, 2, 3], weights=[2, 5, 3], k=1)) # jak długo przebywa w pomieszczeniu, 3 to nadłużej + z.append(random.randint(18, 75)) #od 55 osoba starsza + z.append(random.randint(1, 60)) # jak długo przebywa w pomieszczeniu, od 40 min długo, od 20 min średnio, do 20 min krótko if osoba.kolumna > 21: z.append(0) # zimne pomieszczenie else: