Questions tagged [feature-scaling]

Feature scaling is a data pre-processing step where the range of variable values is standardized. Standardization of datasets is a common requirement for many machine learning algorithms. Popular feature scaling types include scaling the data to have zero mean and unit variance, and scaling the data between a given minimum and maximum value.

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29
votes
3answers
12k views

What is a good way to transform Cyclic Ordinal attributes?

I am having 'hour' field as my attribute, but it takes a cyclic values. How could I transform the feature to preserve the information like '23' and '0' hour are close not far. One way I could think ...
10
votes
2answers
2k views

Linear Regression and scaling of data

The following plot shows coefficients obtained with linear regression (with mpg as the target variable and all others as predictors). For mtcars dataset (here and ...
25
votes
1answer
17k views

Ways to deal with longitude/latitude feature [closed]

I am working on a fictional dataset with 25 features. Two of the features are latitude and longitude of a place and others are pH values, elevation, windSpeed etc with varying ranges. I can perform ...
24
votes
3answers
15k views

Why do we convert skewed data into a normal distribution

I was going through a solution of the Housing prices competition on Kaggle (Human Analog's Kernel on House Prices: Advance Regression Techniques) and came across this part: ...
11
votes
2answers
2k views

Consequence of Feature Scaling

I am currently using SVM and scaling my training features to the range of [0,1]. I first fit/transform my training set and then apply the same transformation to my testing set. For example: ...
6
votes
3answers
659 views

How to give a higher importance to certain features in a (k-means) clustering model?

I am clustering data with numeric and categorical variables. To process the categorical variables for the cluster model, I create dummy variables. However, I feel like this results in a higher ...
2
votes
2answers
80 views

How do standardization and normalization impact the coefficients of linear models?

One benefit of creating a linear model is that you can look at the coefficients the model learns and interpret them. For example, you can see which features have the most predictive power and which do ...