Add prediction

solution.py

@@ -0,0 +1,26 @@
+import numpy
+import pandas
+import sys
+from sklearn.linear_model import LinearRegression
+
+def predict(model, dir):
+    df = pandas.read_csv(dir+"/in.tsv", sep='\t', header=None, index_col=None)
+    input_x = numpy.array(df[1].tolist()).reshape(-1, 1)
+    pred = model.predict(input_x)
+    numpy.savetxt(dir + "/out.tsv", pred, fmt='%d', delimiter='\n')
+
+
+trainCsv = pandas.read_csv("train/train.tsv", sep='\t', header=None, index_col=None)
+data = {
+    'x': trainCsv[2].tolist(), 
+    'y':  trainCsv[0].tolist(),
+}
+
+x = numpy.array(data.get('x')).reshape(-1, 1)
+y = numpy.array(data.get('y')).reshape(-1, 1)
+
+model = LinearRegression()
+model.fit(x, y)
+
+predict(model, "dev-0")
+predict(model, "test-A")