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+#!/usr/bin/python3 + +import pandas as pd +import csv +import pickle +import numpy as np + +def predict(): + dev0 = pd.read_csv("dev-0/in.tsv", delimiter="\t", header=None, names=["document","date"], quoting=csv.QUOTE_NONE)["document"] + testA = pd.read_csv("test-A/in.tsv", delimiter="\t", header=None, names=["document","date"], quoting=csv.QUOTE_NONE)["document"] + + clf = pickle.load(open("clf.model", "rb")) + vectorizer = pickle.load(open("vectorizer.model", "rb")) + + dev0_vectorizer = vectorizer.transform(dev0) + testA_vectorizer = vectorizer.transform(testA) + + y_dev = clf.predict_proba(dev0_vectorizer)[:, 1] + y_test = clf.predict_proba(testA_vectorizer)[:, 1] + + np.savetxt('test-A/out.tsv', y_test, '%f') + np.savetxt('dev-0/out.tsv', y_dev, '%f') + +predict() + diff --git a/test-A/out.tsv b/test-A/out.tsv new file mode 100644 index 0000000..68d2119 --- /dev/null +++ b/test-A/out.tsv @@ -0,0 +1,5153 @@ +0.651363 +0.142776 +0.997645 +0.347984 +0.818897 +0.594240 +0.000487 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