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✨ validate iris data

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0x6f736f646f
2021-01-07 13:33:58 +03:00
parent 3a4e4e00d4
commit a7db9e2e7a
1 changed files with 3 additions and 4 deletions
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Src/Scripts/validateVQC.py
+3 -4
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@@ -226,15 +226,14 @@ class Benchmark:
return self.cost_list
def normalize_data(dataPath="../../Data/Processed/winedata.csv"):
def normalize_data(dataPath = "../../Data/Processed/iris_csv.csv"):
"""
Normalizes the data
:return X_train, X_test, Y_train, Y_test:
"""
# Reads the data
data = pd.read_csv(dataPath)
data = shuffle(data, random_state=42)
X, Y = data[['alcohol', 'flavanoids', 'color_intensity', 'proline']].values, data['target'].values
X, Y = data[['sepal length (cm)', 'sepal width (cm)', 'petal length (cm)', 'petal width (cm)']].values, data['target'].values
# normalize the data
scaler = MinMaxScaler(feature_range=(-2 * np.pi, 2 * np.pi))
X = scaler.fit_transform(X)
@@ -257,7 +256,7 @@ def main():
data_list = "{} {} vdepth {}".format(fe, opt, i)
data[data_list] = test_benchmark.get_cost_list()
w = csv.writer(open("../../Data/Processed/costs.csv", "w"))
w = csv.writer(open("../../Data/Processed/iriscost.csv", "w"))
for key, val in data.items():
w.writerow([key, val])