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 machine-learning
Search options not deleted
user 12417
Machine Learning is a subfield of computer science that draws on elements from algorithmic analysis, computational statistics, mathematics, optimization, etc. It is mainly concerned with the use of data to construct models that have high predictive/forecasting ability. Topics include modeling building, applications, theory, etc.
1
vote
Which, if any, machine learning algorithms are accepted as being a good tradeoff between exp...
Possibly see my answer regarding the unreasonable effectiveness of ensembles, and the tradeoffs on explanation versus prediction. Minimum Message Length (MML, Wallace 2005) gives a formal definition …
- 216
6
votes
Why are ensembles so unreasonably effective
Ensembles win at prediction for theoretical and practical reasons.
There is a fundamental theory of optimal forecasting, if we mean predicting the next event in a sequence based on knowledge of previ …
- 216
1
vote
Using Machine Learning techniques for text-analysis
I think you are asking, for an arbitrary trained classifier, how do you find its mapping between tweet-words and party-probabilities? There are a couple of model-agnostic ways to do this, amounting t …
- 216