diff --git a/.idea/vcs.xml b/.idea/vcs.xml
new file mode 100644
index 0000000..94a25f7
--- /dev/null
+++ b/.idea/vcs.xml
@@ -0,0 +1,6 @@
+
+
+
+
+
+
\ No newline at end of file
diff --git a/.idea/workspace.xml b/.idea/workspace.xml
index 755391e..da73ff3 100644
--- a/.idea/workspace.xml
+++ b/.idea/workspace.xml
@@ -1,7 +1,13 @@
-
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@@ -18,8 +24,8 @@
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@@ -36,6 +42,9 @@
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+
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-
+
+
@@ -80,6 +90,7 @@
+
@@ -124,7 +135,7 @@
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+ C:\Users\jpleb\AppData\Roaming\Subversion
@@ -141,7 +152,7 @@
-
+
@@ -149,7 +160,7 @@
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@@ -159,6 +170,10 @@
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@@ -178,8 +193,8 @@
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diff --git a/dev-0/out.tsv b/dev-0/out.tsv
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+++ b/dev-0/out.tsv
@@ -1,500 +1,500 @@
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diff --git a/my_solution.py b/my_solution.py
index 6337b1e..ba54c48 100644
--- a/my_solution.py
+++ b/my_solution.py
@@ -34,13 +34,13 @@ X_testA = pandas.read_csv('test-A/in.tsv', sep='\t', header=None, names=names)
X_testA.drop('opis', axis=1, inplace=True)
X_testA = encoder(X_testA)
-data_train = X_train[['Powierzchnia w m2', 'Liczba pokoi', 'Miejsce parkingowe', 'Liczba pięter w budynku']].values
+data_train = X_train[['Powierzchnia w m2', 'Liczba pokoi']].values
data_train = np.hstack((data_train, np.ones((data_train.shape[0], 1), dtype=data_train.dtype)))
x = torch.tensor(data_train , dtype=torch.float)
y = torch.tensor(y_train, dtype=torch.float)
-w = torch.tensor([0, 0, 0, 0, 0], dtype=torch.float, requires_grad=True)
+w = torch.tensor([0, 0, 0], dtype=torch.float, requires_grad=True)
learning_rate = torch.tensor(0.00000001)
for _ in range(100000):
@@ -55,13 +55,13 @@ w.requires_grad_(False)
-data_dev = X_dev0[['Powierzchnia w m2', 'Liczba pokoi', 'Miejsce parkingowe', 'Liczba pięter w budynku']].values
+data_dev = X_dev0[['Powierzchnia w m2', 'Liczba pokoi']].values
data_dev = np.hstack((data_dev, np.ones((data_dev.shape[0], 1), dtype=data_dev.dtype)))
x_dev = torch.tensor(data_dev, dtype=torch.float)
-data_testA = X_testA[['Powierzchnia w m2', 'Liczba pokoi', 'Miejsce parkingowe', 'Liczba pięter w budynku']].values
+data_testA = X_testA[['Powierzchnia w m2', 'Liczba pokoi']].values
data_testA = np.hstack((data_testA, np.ones((data_testA.shape[0], 1), dtype=data_testA.dtype)))
x_test = torch.tensor(data_testA , dtype=torch.float)
diff --git a/test-A/out.tsv b/test-A/out.tsv
index dedccd7..252cfca 100644
--- a/test-A/out.tsv
+++ b/test-A/out.tsv
@@ -1,487 +1,487 @@
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