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A group of data scientists want to analyze some data. They already cleaned up the data, with the result being a Dataframe called X_train. The Dataframe X_train has 1058 rows and 13 columns. It has the below columns (picture attached on how it looks like): 'LotFrontage','LotArea','BsmtFinSF1', 'BsmtFinSF2', 'BsmtUnfSF','TotalBsmtSF','1stFlrSF', '2ndFlrSF', 'LowQualFinSF', 'GrLivArea','TotRmsAbvGrd','GarageArea','OpenPorchSF'   Answer the following questions: 1. Transform X_train using PCA. Assign the output to a variable X_train_pca. 2. What is wrong with above approach? Scale the data, then repeat the above.

A group of data scientists want to analyze some data. They already cleaned up the data, with the result being a Dataframe called X_train. The Dataframe X_train has 1058 rows and 13 columns. It has the below columns (picture attached on how it looks like): 'LotFrontage','LotArea','BsmtFinSF1', 'BsmtFinSF2', 'BsmtUnfSF','TotalBsmtSF','1stFlrSF', '2ndFlrSF', 'LowQualFinSF', 'GrLivArea','TotRmsAbvGrd','GarageArea','OpenPorchSF'   Answer the following questions: 1. Transform X_train using PCA. Assign the output to a variable X_train_pca. 2. What is wrong with above approach? Scale the data, then repeat the above.

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A group of data scientists want to analyze some data. They already cleaned up the data, with the result being a Dataframe called X_train. The Dataframe X_train has 1058 rows and 13 columns. It has the below columns (picture attached on how it looks like):

'LotFrontage','LotArea','BsmtFinSF1', 'BsmtFinSF2', 'BsmtUnfSF','TotalBsmtSF','1stFlrSF', '2ndFlrSF', 'LowQualFinSF', 'GrLivArea','TotRmsAbvGrd','GarageArea','OpenPorchSF'

 

Answer the following questions:

1. Transform X_train using PCA. Assign the output to a variable X_train_pca.

2. What is wrong with above approach? Scale the data, then repeat the above.

 

0 1 2 3 4 1452 1453 1454 1455 1459 LotFrontage LotArea BsmtFin SF1 BsmtFinSF2 BsmtUnfSF TotalBsmtSF 1stFlrSF 2nd FlrSF LowQualFin SF 706 854 0 978 486 216 655 65.0 80.0 68.0 60.0 84.0 8450 62.0 75.0 9600 11250 9550 14260 35.0 3675 90.0 17217 62.0 7500 7917 9937 1058 rows x 13 columns ... 547 0 410 0 830 0 0 0 0 0 ooo。 0 0 0 0 290 150 284 434 540 490 0 1140 811 953 136 856 1262 920 756 1145 547 1140 1221 953 1256 856 1262 920 961 1145 1072 1140 1221 953 1256 0 866 756 1053 0 0 0 694 0 0 0 0 0 0 000 00 0 0 GrLivArea TotRmsAbvGrd Garage Area O 548 460 608 642 1710 1262 1786 1717 2198 1072 1140 1221 1647 1256 8 6 6 7 9 5 6 6 7 6 836 525 0 400 460 276
Transcribed Image Text:0 1 2 3 4 1452 1453 1454 1455 1459 LotFrontage LotArea BsmtFin SF1 BsmtFinSF2 BsmtUnfSF TotalBsmtSF 1stFlrSF 2nd FlrSF LowQualFin SF 706 854 0 978 486 216 655 65.0 80.0 68.0 60.0 84.0 8450 62.0 75.0 9600 11250 9550 14260 35.0 3675 90.0 17217 62.0 7500 7917 9937 1058 rows x 13 columns ... 547 0 410 0 830 0 0 0 0 0 ooo。 0 0 0 0 290 150 284 434 540 490 0 1140 811 953 136 856 1262 920 756 1145 547 1140 1221 953 1256 856 1262 920 961 1145 1072 1140 1221 953 1256 0 866 756 1053 0 0 0 694 0 0 0 0 0 0 000 00 0 0 GrLivArea TotRmsAbvGrd Garage Area O 548 460 608 642 1710 1262 1786 1717 2198 1072 1140 1221 1647 1256 8 6 6 7 9 5 6 6 7 6 836 525 0 400 460 276
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