From 565e25fd33f4861fbee6762a3f81d64b248795a1 Mon Sep 17 00:00:00 2001 From: s434732 Date: Mon, 17 May 2021 21:27:15 +0200 Subject: [PATCH] rozwiazanie --- dev-0/out.tsv | 1000 +++++++++++++++++++++++++++++++++++++++++++++++ geval | Bin 0 -> 12638056 bytes rozwiązanie.py | 50 +++ test-A/out.tsv | 1000 +++++++++++++++++++++++++++++++++++++++++++++++ 4 files changed, 2050 insertions(+) create mode 100644 dev-0/out.tsv create mode 100644 geval create mode 100644 rozwiązanie.py create mode 100644 test-A/out.tsv diff --git a/dev-0/out.tsv b/dev-0/out.tsv new file mode 100644 index 0000000..6ff2589 --- /dev/null +++ b/dev-0/out.tsv @@ -0,0 +1,1000 @@ +80410.97631404735 +14322.228104399517 +51118.37913290318 +16995.265404807404 +25183.50176266581 +79781.70195604116 +47955.64834578149 +11525.548448880203 +-5348.3755720909685 +17010.995174583048 +27481.509745324962 +83471.13246457465 +7797.594208772294 +4808.03147051204 +39068.93867867533 +24877.437992001884 +63737.49892832432 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r_expected= './sport-text-classification-ball-ISI-public/train/expected.tsv' +r_ind_ev = './dev-0/in.tsv' + +r_ind_test_A = './test-A/in.tsv' + +with open('./names') as f_names: + names = f_names.read().rstrip('\n').split('\t') + +tsv_read = pandas.read_table(r_in, error_bad_lines=False, sep='\t', names=names) +tsv_read_dev = pandas.read_table(r_ind_ev, error_bad_lines=False, sep='\t', + names=['mileage', 'year', 'brand', 'engineType', 'engineCapacity']) + +tsv_read_test_A = pandas.read_table(r_ind_test_A, error_bad_lines=False, sep='\t', + names=['mileage', 'year', 'brand', 'engineType', 'engineCapacity']) + + +train = pandas.get_dummies(tsv_read, columns=['engineType']) + +categorical_cols = train.select_dtypes(include=object).columns.values +for col in categorical_cols: + train[col] = train[col].astype('category').cat.codes + +train = train.loc[(train['price'] > 1000)] + +X = train.loc[:, train.columns != 'price'] +clf = LinearRegression().fit(X, train['price']) + +dev = pandas.get_dummies(tsv_read_dev, columns=['engineType']) + +categorical_cols1 = dev.select_dtypes(include=object).columns.values +for col in categorical_cols1: + dev[col] = dev[col].astype('category').cat.codes + +predictions = clf.predict(dev) + +predictions.tofile("./dev-0/out.tsv", sep='\n') + +test = pandas.get_dummies(tsv_read_test_A, columns=['engineType']) + +categorical_cols2 = test.select_dtypes(include=object).columns.values +for col in categorical_cols2: + test[col] = test[col].astype('category').cat.codes + +predictions = clf.predict(dev) + +predictions.tofile("./test-A/out.tsv", sep='\n') \ No newline at end of file diff --git a/test-A/out.tsv b/test-A/out.tsv new file mode 100644 index 0000000..6ff2589 --- /dev/null +++ b/test-A/out.tsv @@ -0,0 +1,1000 @@ +80410.97631404735 +14322.228104399517 +51118.37913290318 +16995.265404807404 +25183.50176266581 +79781.70195604116 +47955.64834578149 +11525.548448880203 +-5348.3755720909685 +17010.995174583048 +27481.509745324962 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