From 9f4bb75cf705c51f77db1a3e3f678e4ffb0bd884 Mon Sep 17 00:00:00 2001
From: piotrwrzodak <piotrwrzodakk@gmail.com>
Date: Tue, 27 Jun 2023 19:56:40 +0200
Subject: [PATCH] add zadanie 5 (Biblioteki Deep Learning)

---
 5/main.py                                 |  30 +
 5/model_file.h5                           | Bin 0 -> 97424 bytes
 5/predict.py                              |  15 +
 5/predictions.csv                         | 257 ++++++++
 barcelona_weekends_datasets/dev_set.csv   | 257 ++++++++
 barcelona_weekends_datasets/test_set.csv  | 257 ++++++++
 barcelona_weekends_datasets/train_set.csv | 767 ++++++++++++++++++++++
 main.py                                   |  18 +-
 8 files changed, 1598 insertions(+), 3 deletions(-)
 create mode 100644 5/main.py
 create mode 100644 5/model_file.h5
 create mode 100644 5/predict.py
 create mode 100644 5/predictions.csv
 create mode 100644 barcelona_weekends_datasets/dev_set.csv
 create mode 100644 barcelona_weekends_datasets/test_set.csv
 create mode 100644 barcelona_weekends_datasets/train_set.csv

diff --git a/5/main.py b/5/main.py
new file mode 100644
index 0000000..0cb0a87
--- /dev/null
+++ b/5/main.py
@@ -0,0 +1,30 @@
+import pandas
+import tensorflow as tf
+
+path_to_data = '../barcelona_weekends_datasets/'
+
+if __name__ == '__main__':
+    train_data = pandas.read_csv(path_to_data + 'train_set.csv')
+    dev_data = pandas.read_csv(path_to_data + 'dev_set.csv')
+    test_data = pandas.read_csv(path_to_data + 'test_set.csv')
+
+    x_train, y_train = train_data.iloc[:, :-1], train_data['guest_satisfaction_overall']
+    x_dev, y_dev = dev_data.iloc[:, :-1], dev_data['guest_satisfaction_overall']
+    x_test, y_test = dev_data.iloc[:, :-1], dev_data['guest_satisfaction_overall']
+
+    model = tf.keras.models.Sequential([
+        tf.keras.layers.Dense(64, activation='relu', input_shape=(18,)),
+        tf.keras.layers.Dense(64, activation='relu'),
+        tf.keras.layers.Dense(1, activation='sigmoid')
+    ])
+
+    model.compile(loss='mean_squared_error', optimizer='adam', metrics=['mae'])
+
+    model.fit(x_train, y_train, epochs=10, batch_size=32, validation_data=(x_dev, y_dev))
+
+    loss, mae = model.evaluate(x_test, y_test)
+    print("Test Loss:", loss)
+    print("Test MAE:", mae)
+
+    model.save('model_file.h5')
+
diff --git a/5/model_file.h5 b/5/model_file.h5
new file mode 100644
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diff --git a/5/predict.py b/5/predict.py
new file mode 100644
index 0000000..63d17f4
--- /dev/null
+++ b/5/predict.py
@@ -0,0 +1,15 @@
+import tensorflow as tf
+import pandas as pd
+import numpy as np
+
+if __name__ == '__main__':
+    test_data = pd.read_csv('../barcelona_weekends_datasets/test_set.csv')
+    x_test, y_test = test_data.iloc[:, :-1], test_data['guest_satisfaction_overall']
+
+    model = tf.keras.models.load_model('model_file.h5')
+
+    predictions = model.predict(x_test)
+
+    predictions = np.reshape(predictions, (-1,))
+    df_predictions = pd.DataFrame({'Predictions': predictions})
+    df_predictions.to_csv('predictions.csv', index=False)
diff --git a/5/predictions.csv b/5/predictions.csv
new file mode 100644
index 0000000..e38afdf
--- /dev/null
+++ b/5/predictions.csv
@@ -0,0 +1,257 @@
+Predictions
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diff --git a/barcelona_weekends_datasets/dev_set.csv b/barcelona_weekends_datasets/dev_set.csv
new file mode 100644
index 0000000..77babf8
--- /dev/null
+++ b/barcelona_weekends_datasets/dev_set.csv
@@ -0,0 +1,257 @@
+realSum,room_type,room_shared,room_private,person_capacity,host_is_superhost,multi,biz,cleanliness_rating,bedrooms,dist,metro_dist,attr_index,attr_index_norm,rest_index,rest_index_norm,lng,lat,guest_satisfaction_overall
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diff --git a/barcelona_weekends_datasets/test_set.csv b/barcelona_weekends_datasets/test_set.csv
new file mode 100644
index 0000000..f9d7819
--- /dev/null
+++ b/barcelona_weekends_datasets/test_set.csv
@@ -0,0 +1,257 @@
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diff --git a/barcelona_weekends_datasets/train_set.csv b/barcelona_weekends_datasets/train_set.csv
new file mode 100644
index 0000000..906012d
--- /dev/null
+++ b/barcelona_weekends_datasets/train_set.csv
@@ -0,0 +1,767 @@
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diff --git a/main.py b/main.py
index 3c4f1de..f4c65f6 100644
--- a/main.py
+++ b/main.py
@@ -53,7 +53,11 @@ def normalize_data(data):
     data[numeric_columns] = numeric_data_norm
     data[non_numeric_columns] = non_numeric_data_norm
 
-    return data
+    y_col = 'guest_satisfaction_overall'
+    new_order = list(data.columns.drop(y_col)) + [y_col]
+    new_df = data.reindex(columns=new_order)
+
+    return new_df
 
 
 if __name__ == '__main__':
@@ -86,5 +90,13 @@ if __name__ == '__main__':
     print('Test', calculate_value_counts(test_set, 'person_capacity'), end='\n\n')
 
     # 1.4 & 1.5
-    normalized_data = normalize_data(whole_set)
-    print(normalized_data, '\n\n')
+    whole_set_normalized = normalize_data(whole_set)
+    train_set_normalized = normalize_data(train_set)
+    dev_set_normalized = normalize_data(dev_set)
+    test_set_normalized = normalize_data(test_set)
+    print(whole_set_normalized, '\n\n')
+
+    # Save all sets into files
+    train_set_normalized.to_csv('./barcelona_weekends_datasets/train_set.csv', index=False)
+    dev_set_normalized.to_csv('./barcelona_weekends_datasets/dev_set.csv', index=False)
+    test_set_normalized.to_csv('./barcelona_weekends_datasets/test_set.csv', index=False)