All Questions
Tagged with scikit-learnfeature-scaling
45 questions
1vote
1answer
659views
Inverse Scaling Partitioned Data
I have scaled an original matrix A with sklearn's StandardScaler, resulting to a matrix S. I then partitioned the result into ...
- 11
1vote
1answer
316views
Scale dataset while preserving relative distributions between columns
I have a large dataset with 460 columns. The columns have names such as 'AppOpen_1day', 'AppOpen_2day', ...... 'AppOpen_15day', 'Dig_Pos_1day', 'Dig_Pos_2day', ...... 'DigPos_15day' etc. Each column ...
1vote
1answer
125views
Out-of-Range Target Variable in Sequence-based Machine Learning Model
I'm encountering a scaling issue in a machine learning project. I'm predicting a target variable from an input sequence (and doing this for many). However, I've encountered a challenge where the ...
- 11
2votes
4answers
438views
Are scalers or encoders supposed to be serialized along with trained models?
Consider the very basic example below: ...
2votes
1answer
1kviews
StandardScaler and MinMaxScaler vs RobustScaler
I've recently read that Standard Scaler functions best in situations where the distribution of the features are approximately normal. MinMaxScaler works in a way that it preserves the features' ...
1vote
2answers
1kviews
problem with standardScaler
problem with standardScaler hi I'd like to scale one column in the titanic data set. I am using the following code segment. for some reason df_scaled results an empty set. how can I solve it? what is ...
2votes
4answers
6kviews
why to use Scaler.fit only on x_train and not on x_test for normalizing value using MinMaxScaler?
while normalising the data everone is saying that we need to fit only on x_train and not on x_test ? why is that we should not fit x_test ? if we should not fit the scaler on x_test then why we need ...
- 1,511
0votes
1answer
751views
Feature scaling in Linear Regression
I always use Linearregression() class in sklearn library for creating a linear regression model. According to my understanding, we need feature scaling in linear ...
- 35
1vote
1answer
506views
Is it a good practice to evaluate model performance by comparing the metrics of rescaled (inverse transformed) predictions and true target values?
I am now working with a Linear Regression for a time-series regression problem (I am sorry that I cannot say too much about the problem and feature vector due to NDA). I scaled both the input values ...
- 109
0votes
1answer
8kviews
__init__() takes 1 positional argument but 4 were given sklearn standard scaler error
I defined a class like below: ...
1vote
1answer
37views
0votes
1answer
280views
How to scale a subset of data with respect to the entire dataset
I am developing a financial time-series prediction model using sklearn using StandardScaler for scaling purposes. I train a model, and then use the model regularly ...
- 111
1vote
0answers
24views
Clustering Similar Articles Using Mixed Data: Seeking Advice and Validation
Question: I'm working on a project where I need to cluster a dataset of articles based on various features, including text, numeric values, and categorical data. I've implemented a clustering approach ...
2votes
1answer
4kviews
When and how to use StandardScaler with target data for pre-processing
I am trying to figure out when and how to use scikit-learn's StandardScaler transformer, and how I can apply it to the target variable as well. I've read this post ...
- 85
0votes
1answer
3kviews
For sklearn ML algorithms, is it possible to use boolean data alongside continuous data for the predictive data, and if so how can the data be scaled?
I have a medium size data set (7K) of patient age, sex, and pre-existing conditions. Age of course is from 0-101, sex is 1 for male, 2 for female, and -1 for diverse. All the pre-conditions are ...
- 103
