glmpath

What it is

glmpath is an R package that provides a path of L1 regularized solutions to generalized linear models and Cox proportional hazards model, aiding in feature selection and model fitting with regularization.

glmpath stands out as an R package specifically designed to provide a path of L1 regularized solutions, making it ideal for feature selection in generalized linear models and survival analysis.

When it fits — and when it doesn’t

Known weaknesses

Each one links to the public issue, changelog or docs page it came from, where we have one.

1. 01

   Steep learning curve for non-statisticians

   glmpath requires a strong understanding of statistical concepts such as L1 regularization, generalized linear models, and Cox proportional hazards model.

2. 02

   Limited to R language

   The package is only available in R, which can be a limitation for teams that prefer or are already using other programming languages like Python or Julia.

3. 03

   Sparse community and support

   As an open-source project focused on specialized statistical methods, the user base is relatively small, leading to limited community contributions and slower issue resolution.

4. 04

   Performance limitations with large datasets

   glmpath can be computationally intensive for very large datasets, which may lead to long processing times or memory issues in R.

What it does well

• L1 Regularization Path for Generalized Linear Models

• Supports Cox Proportional Hazards Model

• Feature Selection via Regularization

• Path of Solutions for Different Regularization Parameters

Pricing

Free tier

YesOpen source — free to use

Paid from

$0

Model

Flat rate

Enterprise plan

No

Pricing not independently confirmed — check the vendor’s page.