Fix sample size selection
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@ -35,6 +35,7 @@ def predict_data(data, model, results, sample):
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labels=prediction,
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metric="euclidean",
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sample_size=sample,
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random_state=42,
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)
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populated_results = populate_results(
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df=results,
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@ -80,8 +81,7 @@ def plot_scatter_plot(results):
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def print_dataframe(df):
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df.set_index("model")
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output_df = df.filter["clusters", "silhouette", "calinski", "time"]
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print(output_df)
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print(df)
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def show_results(results):
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@ -95,8 +95,8 @@ def show_results(results):
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def create_result_dataframes():
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results = DataFrame(
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columns=[
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"clusters",
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"model",
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"clusters",
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"prediction",
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"silhouette",
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"calinski-harabasz",
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@ -156,7 +156,7 @@ def main():
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models = ["kmeans", "birch", "affinity", "meanshift", "dbscan"]
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if len(argv) != 4:
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usage()
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case, sample = argv[2], argv[3]
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case, sample = argv[2], int(argv[3])
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data = parse_data(source="data/accidentes_2013.csv", action=str(argv[1]))
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individual_result, complete_results = create_result_dataframes()
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case_data = construct_case(df=data, choice=case)
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@ -171,8 +171,8 @@ def main():
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complete_results = complete_results.append(
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individual_result.append(model_results)
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)
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indexed_results = complete_results.set_index("model")
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show_results(results=indexed_results)
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complete_results.set_index("model")
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print_dataframe(df=complete_results)
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if __name__ == "__main__":
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