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The tutorial says "A state of the art algorithm for text classification is Multinomial Naive Bayes. This is a probabilistic learning method which calculates the probability of a document being in a ca…
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Hi,
I am about to have a relatively big dataset (100K rows) with about 200 features and lots of edges. I was considering pgmpy as the bayesnet constructor and engine.
Can it handle this about of d…
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-Build models and track their accuracy
-Provide cost analysis and metrics for each architecture tried
-Pick best performing model
child of #19
connects #19
danqo updated
5 years ago
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We need to create a multinomial naive bayes for `hw8/assignment.R`.
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I am finding the optimal value of hyperparameter alpha for my Multinpmial Naive Bayes model which uses cross validation and neg_log_loss as metric. I wrote this code:
```
alphas = list(range(1, 50…
ghost updated
5 years ago
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Write a test that does not include negative feature values.
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Perhaps we shouldn't add the log prod of each features directly onto each other before normalization.
For example, a very small sigma on a gaussian feature will create a very large negative value o…
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Currently the common test hard-code many things, like support for multi-output, or requiring positive input, or not allowing specific kinds of predictions.
That's bad design, but also a big problem f…
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Hello,
Following up on some `gitter` chat with @kevinykuo
Here is the issue. When I train my Naive Bayes model:
```
mymodel % select(myday,headline, type) %>%
filter(!is.na(headline)) %…
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I am trying to set up naive Bayes learners(bernoulli and multinomial), how do i set up the vectorizers for two separate situations?
- presence or non presence in feature vector
- the count of wor…
jzyee updated
6 years ago