Search Results
| Search type | Search syntax |
|---|---|
| Tags | [tag] |
| Exact | "words here" |
| Author |
user:1234 user:me (yours) |
| Score |
score:3 (3+) score:0 (none) |
| Answers |
answers:3 (3+) answers:0 (none) isaccepted:yes hasaccepted:no inquestion:1234 |
| Views | views:250 |
| Code | code:"if (foo != bar)" |
| Sections |
title:apples body:"apples oranges" |
| URL | url:"*.example.com" |
| Saves | in:saves |
| Status |
closed:yes duplicate:no migrated:no wiki:no |
| Types |
is:question is:answer |
| Exclude |
-[tag] -apples |
| For more details on advanced search visit our help page | |
Results tagged with scikit-learn
Search options not deleted
user 50519
scikit-learn is a popular machine learning package for Python that has simple and efficient tools for predictive data analysis. Topics include classification, regression, clustering, dimensionality reduction, model selection, and preprocessing.
0
votes
Which algorithm is used in sklearn SGDClassifier when modified huber loss is used?
The modified Huber loss is equivalent to a quadratically smoothed SVM with gamma = 2.
See also https://www.quora.com/What-algorithm-is-used-in-sklearn%E2%80%99s-SGDClassifier-when-a-modified-huber-los …
- 431
0
votes
1
answer
317
views
How can I train a decision tree constrained to have number of decision nodes = tree depth?
In order to make a classifier dead easy to understand/interpret, I want to classify tabular data (with n columns) according to a set of nested rules, with the constraint that the number of decision no …
- 431
1
vote
Accepted
How to calculate Accuracy, Precision, Recall and F1 score based on predict_proba matrix?
To compute performance metrics like precision, recall and F1 score you need to compare two things with each other:
the predictions of your model for your evaluation set (in what follows, I'll call …
- 431