DecisionTree save and load from file
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@ -4,6 +4,7 @@ import pydotplus
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from sklearn.tree import DecisionTreeClassifier
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import matplotlib.pyplot as plt
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import matplotlib.image as pltimg
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import joblib
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df = pandas.read_csv("treedata\\data.csv")
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@ -38,12 +39,14 @@ y = df['Decision']
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dtree = DecisionTreeClassifier()
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dtree = dtree.fit(X, y)
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joblib.dump(dtree, 'treedata\\DecisionTree.pkl')
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data = tree.export_graphviz(dtree, out_file=None, feature_names=features)
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graph = pydotplus.graph_from_dot_data(data)
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graph.write_png('mydecisiontree.png')
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graph.write_png('treedata\\mydecisiontree.png')
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img = pltimg.imread('mydecisiontree.png')
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img = pltimg.imread('treedata\\mydecisiontree.png')
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imgplot = plt.imshow(img)
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plt.show()
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5
main.py
5
main.py
@ -7,11 +7,11 @@ import WeatherConditions
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import convertToPrediction
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import drawUI
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import Graphsearch as graph
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from decisiontree import dtree
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from Tractor import Tractor
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from TractorLoad import TillageUnit
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from constants import *
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from manualSteering import manualSteeringDriver
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import joblib
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pygame.init()
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@ -58,6 +58,9 @@ while working:
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weather, day_time, temperature, wind, humidy = WeatherConditions.checkConditions()
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question = [convertToPrediction.convert(field.state, weather, day_time, temperature, wind, humidy)]
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dtree = joblib.load('treedata\\DecisionTree.pkl')
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decision = dtree.predict(question)
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if tractor.autodrive:
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BIN
treedata/DecisionTree.pkl
Normal file
BIN
treedata/DecisionTree.pkl
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