AppliedPredictiveModeling | : exclamation : This is a read-only mirror of the CRAN R | Data Visualization library

by cran R Version: 1.1-7 License: No License

X-Ray Key Features Code Snippets Community Discussions(4)Vulnerabilities Install Support

kandi X-RAY | AppliedPredictiveModeling Summary

AppliedPredictiveModeling is a R library typically used in Analytics, Data Visualization applications. AppliedPredictiveModeling has no bugs, it has no vulnerabilities and it has low support. You can download it from GitHub.

:exclamation: This is a read-only mirror of the CRAN R package repository. AppliedPredictiveModeling — Functions and Data Sets for 'Applied Predictive Modeling'. Homepage: http://appliedpredictivemodeling.com/

Support

Quality

Security

License

Reuse

Support

AppliedPredictiveModeling has a low active ecosystem.

It has 54 star(s) with 64 fork(s). There are 9 watchers for this library.

It had no major release in the last 6 months.

AppliedPredictiveModeling has no issues reported. There are no pull requests.

It has a neutral sentiment in the developer community.

The latest version of AppliedPredictiveModeling is 1.1-7

Quality

AppliedPredictiveModeling has 0 bugs and 0 code smells.

Security

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

AppliedPredictiveModeling code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

AppliedPredictiveModeling 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

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

Top functions reviewed by kandi - BETA

kandi's functional review helps you automatically verify the functionalities of the libraries and avoid rework.
Currently covering the most popular Java, JavaScript and Python libraries. See a Sample of AppliedPredictiveModeling

Get all kandi verified functions for this library.

AppliedPredictiveModeling Key Features

No Key Features are available at this moment for AppliedPredictiveModeling.

AppliedPredictiveModeling Examples and Code Snippets

No Code Snippets are available at this moment for AppliedPredictiveModeling.

Community Discussions

Trending Discussions on AppliedPredictiveModeling

Error: BoxCox error during preprocess imputation R language

How do I specify a PLS model in tidy models

Predictor importance for PLS model trained with tidymodels

Tidymodels : problem performing PCR Error: Can't subset columns that don't exist

QUESTION

Error: BoxCox error during preprocess imputation R language

Asked 2021-Mar-20 at 09:54

I am looking at the answers to the Chapter 6 exercise 3 questions from the Applied Predictive Modeling book Max Kuhn and I am getting an error in the imputation prediction step (despite following their answer exactly). The reproducible code and problem is as follows:

...

ANSWER

Answered 2021-Mar-20 at 09:54

You get that error because the boxcox transformation does not take in zero. If you check the help page for BoxCoxTrans it writes:

If any(y <= 0) or if length(unique(y)) < numUnique, lambda is not estimated and no transformation is applied.

So if your preProcess() is run on a train set with no zeros in the columns, the boxcox transformation is applied, but it will not work on a test set with zeros.

In the book example above, most likely the seed was set with an older R version, so it works. If you are using a newer version of R, then it doesn't work. So if I check with your example:

Source https://stackoverflow.com/questions/66692652

QUESTION

How do I specify a PLS model in tidy models

Asked 2020-Nov-12 at 22:12

I'm interested in learning tidymodels and have tried to apply it to some exercises in Appied Predictive Modeling. This is Exercise 6.2. I would like to specify a Partial Least Squares (PLS) model to the permeability data set.

I have the following code that works all the way up to the tune grid. I've modeled my analysis off of Julia Silge's - Lasso regression with tidymodels and The Office found here.

You can see my script and the tune_grid error message below.

...

ANSWER

Answered 2020-Nov-12 at 22:12

I am guessing that you may be using a Windows computer, because we currently have a bug in the CRAN version of tune for parallel processing on Windows. Try either:

training sequentially without parallel processing, or
installing the development version of tune where we have fixed this bug, via devtools::install_github("tidymodels/tune")

You should see results like this:

Source https://stackoverflow.com/questions/64582463

QUESTION

Predictor importance for PLS model trained with tidymodels

Asked 2020-Oct-19 at 19:20

I'm using tidymodels to fit a PLS model but I'm struggling to find the PLS variable importance scores or coefficients.

This is what I've tried so far; the example data is from AppliedPredictiveModeling package.

Modeling fitting ...

ANSWER

Answered 2020-Oct-19 at 19:20

You can directly tidy() the output of the PLS model to get the coefficients:

Source https://stackoverflow.com/questions/64254295

QUESTION

Tidymodels : problem performing PCR Error: Can't subset columns that don't exist

Asked 2020-Sep-20 at 10:21

I'm trying to do a PCR with tidymodels however i'm keep runing into this problem. I know there is a similar post but the solution over there, doesn't work form my case.

My data

...

ANSWER

Answered 2020-Sep-20 at 10:21

It is because workflow needs a recipe specification that is not prepped.

So, in your code, removing the prep() from the recipe specification will eliminate the error.

Source https://stackoverflow.com/questions/63974520

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

Vulnerabilities

No vulnerabilities reported

Install AppliedPredictiveModeling

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 .

Find more information at: