New answers tagged

0 votes

How "normal" should my input data be?

The objective of standardization is that the values of features must be comparable. for example in housing price prediction the number of rooms and the size of house are very different and we need ...
user avatar
  • 141
0 votes

Difference between OrdinalEncoder and LabelEncoder

You can encode multiple columns at once using OrdinalEncoder, while LabelEncoder can handle only one column. e.g. ...
user avatar
0 votes

Forecast multiple unevenly spaced time series

"Is there a golden standard for equalizing time series observations?" Ans.: No. But there are some approaches. A time-series where the events occur in arbitrary time can be approached ...
user avatar
  • 101
2 votes

Lost human names after 'Lemmatization' for topic modeling in python

Names qualify as a 'PROPN' postag. Adding it to the allowed_postags list should likely fix the issue. Edit: a simplified example ...
user avatar
  • 391
1 vote

What Preprocessing is Needed for Semantic Search Using Pre-trained Hugging Face Transformers?

Resumes are quite different from classic text because there are many proper nouns (names, companies, places, etc.) and other data difficult to classify (phone numbers, marks, age, etc.). That's why ...
user avatar
1 vote

Getting equal distributions of data from different input sets

Imho it's possible that you're overthinking this: Easy option: regular sampling concatenate all three lists together, then shuffle the dataset and then take the first 70% elements as training set, the ...
user avatar
  • 22.2k
0 votes

Data preprocessing for Multiple Linear Regression Problem

https://stats.stackexchange.com/questions/484299/how-to-check-the-correlation-between-categorical-and-numeric-independent-variabl/484300#484300 This link mentions a couple of approaches (albiet in R, ...
user avatar
  • 149

Top 50 recent answers are included