f72b08625855cf00d3238fa43955819e428378e9,notebooks/benchmark.py,,,#,16

Before Change

    time_list = time_list + np.mean(time_mat, axis=0).tolist()
    temp_df = pd.DataFrame(time_list).transpose()
    temp_df.columns = df_columns
    time_df = pd.concat([time_df, temp_df], axis=0)

    roc_list = roc_list + np.mean(roc_mat, axis=0).tolist()
    temp_df = pd.DataFrame(roc_list).transpose()
    temp_df.columns = df_columns
    roc_df = pd.concat([roc_df, temp_df], axis=0)

    prn_list = prn_list + np.mean(prn_mat, axis=0).tolist()
    temp_df = pd.DataFrame(prn_list).transpose()
    temp_df.columns = df_columns
    prn_df = pd.concat([prn_df, temp_df], axis=0)

// No need to save locally
// time_df.to_excel("time.xlsx", index=False)
// roc_df.to_excel("roc.xlsx", index=False)
// prn_df.to_excel("prc.xlsx", index=False)

time_df.to_csv("time.csv", index=False)
roc_df.to_csv("roc.csv", index=False)
prn_df.to_csv("prc.csv", index=False)

After Change

    time_list = time_list + np.mean(time_mat, axis=0).tolist()
    temp_df = pd.DataFrame(time_list).transpose()
    temp_df.columns = df_columns
    time_df = pd.concat([time_df, temp_df], axis=0)

    roc_list = roc_list + np.mean(roc_mat, axis=0).tolist()
    temp_df = pd.DataFrame(roc_list).transpose()
    temp_df.columns = df_columns
    roc_df = pd.concat([roc_df, temp_df], axis=0)

    prn_list = prn_list + np.mean(prn_mat, axis=0).tolist()
    temp_df = pd.DataFrame(prn_list).transpose()
    temp_df.columns = df_columns
    prn_df = pd.concat([prn_df, temp_df], axis=0)

    // Save the results for each run
    time_df.to_csv("time.csv", index=False, float_format="%.3f")
    roc_df.to_csv("roc.csv", index=False, float_format="%.3f")
    prn_df.to_csv("prc.csv", index=False, float_format="%.3f")

Instances