SimpleLM | standalone python classes for training statistical language | Machine Learning library

by AdolfVonKleist Python Version: Current License: No License

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

kandi X-RAY | SimpleLM Summary

SimpleLM is a Python library typically used in Artificial Intelligence, Machine Learning applications. SimpleLM has no bugs, it has no vulnerabilities and it has low support. However SimpleLM build file is not available. You can download it from GitHub.

Simple, standalone python classes for training statistical language models using several popular smoothing methods. Also includes a script for evaluating LM sentence probabilities and retrieving individual NGram probabilities.

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SimpleLM has a low active ecosystem.

It has 21 star(s) with 8 fork(s). There are 6 watchers for this library.

It had no major release in the last 6 months.

There are 1 open issues and 0 have been closed. On average issues are closed in 2841 days. There are no pull requests.

It has a neutral sentiment in the developer community.

The latest version of SimpleLM is current.

Quality

SimpleLM has no bugs reported.

Security

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

License

SimpleLM 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

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

SimpleLM has no build file. You will be need to create the build yourself to build the component from source.

Installation instructions are not available. Examples and code snippets are available.

Top functions reviewed by kandi - BETA

kandi has reviewed SimpleLM and discovered the below as its top functions. This is intended to give you an instant insight into SimpleLM implemented functionality, and help decide if they suit your requirements.

Push a word onto the stack
Remove the element from the list

Get all kandi verified functions for this library.

SimpleLM Key Features

No Key Features are available at this moment for SimpleLM.

SimpleLM Examples and Code Snippets

No Code Snippets are available at this moment for SimpleLM.

Community Discussions

Trending Discussions on SimpleLM

Fast pairwise simple linear regression between variables in a data frame

ggplot error: Found object is not a stat

QUESTION

Fast pairwise simple linear regression between variables in a data frame

Asked 2018-Oct-02 at 22:33

I have seen pairwise or general paired simple linear regression many times on Stack Overflow. Here is a toy dataset for this kind of problem.

...

ANSWER

Answered 2018-Aug-26 at 19:26

Some statistical result / background

(Link in the picture: Function to calculate R2 (R-squared) in R)

Computational details

Computations involved here is basically the computation of the variance-covariance matrix. Once we have it, results for all pairwise regression is just element-wise matrix arithmetic.

The variance-covariance matrix can be obtained by R function cov, but functions below compute it manually using crossprod. The advantage is that it can obviously benefit from an optimized BLAS library if you have it. Be aware that significant amount of simplification is made in this way. R function cov has argument use which allows handling NA, but crossprod does not. I am assuming that your dat has no missing values at all! If you do have missing values, remove them yourself with na.omit(dat).

The initial as.matrix that converts a data frame to a matrix might be an overhead. In principle if I code everything up in C / C++, I can eliminate this coercion. And in fact, many element-wise matrix matrix arithmetic can be merged into a single loop-nest. However, I really bother doing this at the moment (as I have no time).

Some people may argue that the format of the final return is inconvenient. There could be other format:

a list of data frames, each giving the result of the regression for a particular LHS variable;
a list of data frames, each giving the result of the regression for a particular RHS variable.

This is really opinion-based. Anyway, you can always do a split.data.frame by "LHS" column or "RHS" column yourself on the data frame I return you.

R function pairwise_simpleLM

Source https://stackoverflow.com/questions/51953709

QUESTION

ggplot error: Found object is not a stat

Asked 2017-May-01 at 18:36

ggplot() +
  geom_point(aes(x = Africa_set$Africa_Predict, y = Africa_set$Africa_Real), color ="red") +
  geom_line(aes(x = Africa_set$Africa_Predict, y = predict(simplelm, newdata = Africa_set)),color="blue") +
  labs(title = "Africa Population",fill="") +
  xlab("Africa_set$Africa_Predict") + 
  ylab("Africa_set$Africa_Real")

...

ANSWER

Answered 2017-May-01 at 18:34

It looks like you are trying to plot points with a fitted regression line on top. You can do this using:

Source https://stackoverflow.com/questions/43723464

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

Vulnerabilities

No vulnerabilities reported

Install SimpleLM

You can download it from GitHub.
You can use SimpleLM like any standard Python library. You will need to make sure that you have a development environment consisting of a Python distribution including header files, a compiler, pip, and git installed. Make sure that your pip, setuptools, and wheel are up to date. When using pip it is generally recommended to install packages in a virtual environment to avoid changes to the system.

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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