forked from kubapok/auta-public
change config.txt
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@ -1 +1 @@
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--precision 1
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--metric RMSE --precision 1
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@ -1,4 +1,3 @@
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0
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77497.59817308374
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77497.59817308374
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12145.183204738423
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12145.183204738423
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49614.760815142654
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49614.760815142654
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5
main.py
5
main.py
@ -35,7 +35,8 @@ cars_dev.drop('brand', inplace=True, axis=1)
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X_dev = pd.DataFrame(cars_dev)
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X_dev = pd.DataFrame(cars_dev)
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Y_dev_predicted = model.predict(X_dev)
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Y_dev_predicted = model.predict(X_dev)
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pd.DataFrame(Y_dev_predicted).to_csv('dev-0/out.tsv', sep='\t', index=False)
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print(Y_dev_predicted)
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pd.DataFrame(Y_dev_predicted).to_csv('dev-0/out.tsv', sep='\t', index=False, header=False)
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cars_test=pd.read_csv('test-A/in.tsv', sep='\t', names=names)
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cars_test=pd.read_csv('test-A/in.tsv', sep='\t', names=names)
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@ -44,7 +45,7 @@ cars_test.drop('brand', inplace=True, axis=1)
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X_test = pd.DataFrame(cars_test)
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X_test = pd.DataFrame(cars_test)
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Y_test_predicted = model.predict(X_test)
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Y_test_predicted = model.predict(X_test)
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pd.DataFrame(Y_test_predicted).to_csv('test-A/out.tsv', sep='\t', index=False)
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pd.DataFrame(Y_test_predicted).to_csv('test-A/out.tsv', sep='\t', index=False, header=False)
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error = np.sqrt(mean_squared_error(Y_dev, Y_dev_predicted))
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error = np.sqrt(mean_squared_error(Y_dev, Y_dev_predicted))
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print(error)
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print(error)
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@ -1,4 +1,3 @@
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0
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24338.076058211736
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24338.076058211736
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23636.277893734165
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23636.277893734165
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12031.8488286715
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12031.8488286715
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