what are the pros and cons to zscore a dataset before normalize it during feature engineering?2019 Community Moderator ElectionHow to perform feature engineering on unknown features?What are the strategies for feature engineering in a hierarchical/relational structured data?Automatic Feature EngineeringRegression for binary classification and AUC metricHow To Merge Features in the Dataset Forest Cover Type Classification Problem?What feature engineering is necessary with tree based algorithms?What are best practices for collaborative feature engineering?Why normalize when all features are on the same scale?Is it ok to train the model only on the interested part of the data?Manual feature engineering based on the output
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what are the pros and cons to zscore a dataset before normalize it during feature engineering?
2019 Community Moderator ElectionHow to perform feature engineering on unknown features?What are the strategies for feature engineering in a hierarchical/relational structured data?Automatic Feature EngineeringRegression for binary classification and AUC metricHow To Merge Features in the Dataset Forest Cover Type Classification Problem?What feature engineering is necessary with tree based algorithms?What are best practices for collaborative feature engineering?Why normalize when all features are on the same scale?Is it ok to train the model only on the interested part of the data?Manual feature engineering based on the output
$begingroup$
normalization is a common feature engineering technique. but this post standardize(zscore) a dataset before normalize it.
I think that would result in losing some info in data.
what are the pros and cons to do this?
machine-learning feature-engineering
$endgroup$
add a comment |
$begingroup$
normalization is a common feature engineering technique. but this post standardize(zscore) a dataset before normalize it.
I think that would result in losing some info in data.
what are the pros and cons to do this?
machine-learning feature-engineering
$endgroup$
add a comment |
$begingroup$
normalization is a common feature engineering technique. but this post standardize(zscore) a dataset before normalize it.
I think that would result in losing some info in data.
what are the pros and cons to do this?
machine-learning feature-engineering
$endgroup$
normalization is a common feature engineering technique. but this post standardize(zscore) a dataset before normalize it.
I think that would result in losing some info in data.
what are the pros and cons to do this?
machine-learning feature-engineering
machine-learning feature-engineering
asked 30 mins ago
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fu DLfu DL
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