forgettable | Various implementations of the forget table | Form library

by bitly Go Version: 0.1.0 License: No License

X-Ray Key Features Code Snippets(2)Community Discussions(2)Vulnerabilities Install Support

kandi X-RAY | forgettable Summary

forgettable is a Go library typically used in User Interface, Form, Kafka applications. forgettable has no bugs, it has no vulnerabilities and it has low support. You can download it from GitHub.

Forget-Table is a database for storing non-stationary categorical distributions that forget old observations responsibly. It has been designed to store millions of distributions and can be written to at a high volume.

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Support

forgettable has a low active ecosystem.

It has 204 star(s) with 22 fork(s). There are 28 watchers for this library.

It had no major release in the last 12 months.

There are 0 open issues and 3 have been closed. On average issues are closed in 41 days. There are 2 open pull requests and 0 closed requests.

It has a neutral sentiment in the developer community.

The latest version of forgettable is 0.1.0

Quality

forgettable has no bugs reported.

Security

forgettable has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

License

forgettable does not have a standard license declared.

Check the repository for any license declaration and review the terms closely.

Without a license, all rights are reserved, and you cannot use the library in your applications.

Reuse

forgettable releases are not available. You will need to build from source code and install.

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forgettable Key Features

No Key Features are available at this moment for forgettable.

forgettable Examples and Code Snippets

Difficulties to get the correct posterior value in a Naive Bayes Implementation

Python

Lines of Code : 3

License : Strong Copyleft (CC BY-SA 4.0)

Copy

prior = (data_frame.label == l).mean()
results.append([l,prior*math.prod(p)])

UnicodeError on uploading dataframe to_csv file buffer to Google Cloud Storage

Python

Lines of Code : 21

License : Strong Copyleft (CC BY-SA 4.0)

Copy

blob = Blob(blob_path, bucket)
blob.upload_from_file(buffer, content_type=content_type)

def _encode(data, name='data'):
    """Call data.encode("latin-1") but show a better error message."""
    try:
        return

Community Discussions

Trending Discussions on forgettable

Difficulties to get the correct posterior value in a Naive Bayes Implementation

How to fix this `group_by` statement

QUESTION

Difficulties to get the correct posterior value in a Naive Bayes Implementation

Asked 2020-Nov-12 at 14:44

For studying purposes, I've tried to implement this "lesson" using python but "without" sckitlearn or something similar.

My attempt code is the follow:

...

ANSWER

Answered 2020-Nov-12 at 11:43

You haven't multiplied by the priors p(Sport) = 3/5 and p(Not Sport) = 2/5. So just updating your answers by these ratios will get you to the correct result. Everything else looks good.

So for example you implement p(a|Sports) x p(very|Sports) x p(close|Sports) x p(game|Sports) in your math.prod(p) calculation but this ignores the term p(Sport). So adding this in (and doing the same for the not sport condition) fixes things.

In code this can be achieved by:

Source https://stackoverflow.com/questions/64745233

QUESTION

How to fix this `group_by` statement

Asked 2019-May-03 at 20:07

I'm am having an issue with a simple dplyr, group_by and summarise chain.

I have a tibble with 542 procedures performed for different diagnoses. Here are two selected columns:

...

ANSWER

Answered 2019-May-03 at 20:07

As was mentioned previously by the OP, the use of a 0 index is breaking the code.

This solution uses two packages from the tidyverse. You will need to load the following:

Source https://stackoverflow.com/questions/55975623

Community Discussions, Code Snippets contain sources that include Stack Exchange Network

Vulnerabilities

No vulnerabilities reported

Install forgettable

You can download it from GitHub.

Support

For any new features, suggestions and bugs create an issue on GitHub. If you have any questions check and ask questions on community page Stack Overflow .

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