Skip to main content
Cross Validated

Return to Question

Notice removed Draw attention by CommunityBot
Bounty Ended with no winning answer by CommunityBot
Tweeted twitter.com/StackStats/status/665194197478195200
Notice added Draw attention by Escachator
Bounty Started worth 50 reputation by Escachator
removed unnecessary manners
Source Link
edit approved Nov 1, 2015 at 18:43
jona
edit approved Nov 1, 2015 at 18:43
jona
  • 1.9k
  • 13
  • 22

I am fitting a logistic regression model with a set of features for predicting outcomes in football games (three outcomes available: home wins, away wins or draw).

The features are such as difference in position in the league table between the home team and the away team, difference in previous 10 games number of wins... So they can be positive as well as negative.

I would like to do a goodness of fit of this features. I understand that the correct way of doing it is using the Pearson chi squared test, however this test is used when the features are observed frequencies, which is not my case.

Is there any other test that I can use, or a way of modifying my test to understand how good my features are?

Thank you!

I am fitting a logistic regression model with a set of features for predicting outcomes in football games (three outcomes available: home wins, away wins or draw).

The features are such as difference in position in the league table between the home team and the away team, difference in previous 10 games number of wins... So they can be positive as well as negative.

I would like to do a goodness of fit of this features. I understand that the correct way of doing it is using the Pearson chi squared test, however this test is used when the features are observed frequencies, which is not my case.

Is there any other test that I can use, or a way of modifying my test to understand how good my features are?

Thank you!

I am fitting a logistic regression model with a set of features for predicting outcomes in football games (three outcomes available: home wins, away wins or draw).

The features are such as difference in position in the league table between the home team and the away team, difference in previous 10 games number of wins... So they can be positive as well as negative.

I would like to do a goodness of fit of this features. I understand that the correct way of doing it is using the Pearson chi squared test, however this test is used when the features are observed frequencies, which is not my case.

Is there any other test that I can use, or a way of modifying my test to understand how good my features are?

Source Link
Escachator
Escachator
  • 250
  • 2
  • 13

Goodness of fit in logistic regression where features are not frequencies

I am fitting a logistic regression model with a set of features for predicting outcomes in football games (three outcomes available: home wins, away wins or draw).

The features are such as difference in position in the league table between the home team and the away team, difference in previous 10 games number of wins... So they can be positive as well as negative.

I would like to do a goodness of fit of this features. I understand that the correct way of doing it is using the Pearson chi squared test, however this test is used when the features are observed frequencies, which is not my case.

Is there any other test that I can use, or a way of modifying my test to understand how good my features are?

Thank you!