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 6478
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.
2
votes
Should I use a cleaned labeled data for sentiment analysis?
The OP asks "Does cleaning of data before labeling make any difference?" - that's an empirical question... one that should be investigated by EDA of your data.
In some cases twitter-specific convent …
- 1,216
3
votes
Classifier Chains
The OP reports that when a series of one-vs-rest classifiers are chained together in an ensemble from most accurate to least, the overall predictive accuracy of the ensemble decreases compared to the …
- 1,216
1
vote
How to find a changing relation between continuous variables?
Besides doing initial EDA and plotting dependent vs independent variables, it would seem prudent to try to first identify the "maintenance" points. According to your description of the problem, we can …
- 1,216
3
votes
Twitter Sentiment Analysis: Detecting neutral tweets despite training on only Positive and N...
The quick (and not very satisfying) answer is "it depends" -- specifically it depends upon what your underlying conceptual model of human emotion is and how it manifests in verbal/written behavior.
…
- 1,216
2
votes
Multiclass classification with large number of classes but for each user the set of target c...
so it sounds like you have historical transaction data. If you do, you probably want to train a model using store label as your dependent variable, and all the others independent variables.
set.seed …
- 1,216
4
votes
What algorithm is used to extract keywords from unstructured texts?
The OP asks two different questions: (1) how to extract key words and (2) how to assign keywords a sentiment class (pos/neg/neu). I will address the keyword identification piece in this answer as many …
- 1,216
13
votes
Accepted
How to determine if character sequence is English word or noise
During NLP and text analytics, several varieties of features can be extracted from a document of words to use for predictive modeling. These include the following.
ngrams
Take a random sample of wor …
- 1,216
8
votes
Accepted
Ideas for prospect scoring model
I faced almost exactly the same scenario a year and a half ago -- basically what you have is a variation of the one-class classification (OCC) problem, specifically PU-learning (learning from Positive …
- 1,216
1
vote
Which features do I select from text?
A feature extractor is just a function that returns the value of a feature given a target instance. For example, given in the input sentence "I friggin hate regex", you could run a tokenizer on it to …
- 1,216
3
votes
How to perform model selection for One-Class Classification?
Have you read Janssens' dissertation "Outlier Selection and One-Class Classification"? He has a chapter on evaluation which may be of use. Have you thought about artificial generation of negative inst …
- 1,216
3
votes
Categorizing Customer Emails
(1) Data quality. The single best way to improve your accuracy. Garbage in garbage out. You already said your data is suspect. Some data was mis-classified; data only has single label, when multiple l …
- 1,216