Elad Rapaport erap129
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| train_df.drop(columns=['sensor_25', 'sensor_26'], inplace=True) | |
| SENSOR_COLUMN_NAMES.remove('sensor_25') | |
| SENSOR_COLUMN_NAMES.remove('sensor_26') |
We can make this file beautiful and searchable if this error is corrected: It looks like row 4 should actually have 20 columns, instead of 18 in line 3.
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| ,unit_number,time,sensor_1,sensor_2,sensor_5,sensor_6,sensor_7,sensor_10,sensor_11,sensor_12,sensor_14,sensor_15,sensor_16,sensor_17,sensor_18,sensor_20,sensor_23,sensor_24,RUL | |
| count,20631.0,20631.0,20631.0,20631.0,20631.0,20631.0,20631.0,20631.0,20631.0,20631.0,20631.0,20631.0,20631.0,20631.0,20631.0,20631.0,20631.0,20631.0,20631.0 | |
| mean,51.506567786340945,108.80786195530997,0.4994902214444654,0.5019590260611053,0.4430522730736785,0.42474642703118026,0.45043520742321874,0.5664591322518506,0.29795703141632884,0.1952478718490331,0.41140961013362015,0.5806972325890045,0.3178711647518692,0.2260951703849851,0.4511180526792186,0.4342211558657721,0.5242408222141806,0.5461272588576589,107.80786195530997 | |
| std,29.227632908799837,68.88099017721818,0.12570766948363188,0.24421843713843072,0.15061845483753925,0.13366360409179906,0.15193458441160862,0.14252693360119403,0.1075537558953646,0.09908857365640435,0.1589805944283841,0.1572608512174252,0.10576311132144779,0.09844243975618262,0.14430564814146393,0.12906358538452264,0 |
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| # for reproducibility | |
| pl.seed_everything(42) | |
| train_df = pd.read_csv('/content/drive/MyDrive/Datasets/NASA_CMAPSS/train_FD001.txt', delimiter=' ', header=None) | |
| test_df = pd.read_csv('/content/drive/MyDrive/Datasets/NASA_CMAPSS/test_FD001.txt', delimiter=' ', header=None) | |
| SENSOR_COLUMN_NAMES = [f'sensor_{i}' for i in range(1, 27)] | |
| df_columns = ['unit_number', 'time', *SENSOR_COLUMN_NAMES] | |
| train_df.columns = df_columns | |
| test_df.columns = df_columns | |
| train_df.describe() |
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| import numpy as np | |
| import pandas as pd | |
| import plotly.express as px | |
| from xgboost import XGBRegressor | |
| from sklearn.preprocessing import MinMaxScaler | |
| from sklearn.metrics import mean_squared_error | |
| from sklearn.linear_model import LinearRegression | |
| from sklearn.model_selection import train_test_split | |
| import tsfresh | |
| from tsfresh import select_features |
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