mboost
mboost implements a functional gradient descent algorithm for optimizing general risk functions through component-wise (penalised) least squares or regression trees. It a... mboost implements a functional gradient descent algorithm for optimizing general risk functions through component-wise (penalised) least squares or regression trees. It accommodates user-defined loss functions and base-learners for fitting generalized linear, additive, and interaction models, making it suitable for high-dimensional data analysis. More information can be found at https://CRAN.R-project.org/package=mboost.
Top mboost Alternatives
maptree
Maptree is a sophisticated machine learning software that facilitates graphing, pruning, and mapping models derived from hierarchical clustering, as well...
partykit
Partykit offers a robust toolkit for representing, summarizing, and visualizing tree-structured regression and classification models. It facilitates seamless integration with...
Cubist
Cubist is a machine learning software that specializes in regression modeling through rule-based approaches enhanced by instance-based corrections. It effectively...
rgenoud
rgenoud is an advanced machine learning software that integrates a genetic algorithm with a derivative optimizer, enabling efficient global optimization....
C5.0: Decision Trees and Rule-Based Models
C5.0 is a robust machine learning software that builds upon Quinlan's foundational work in decision trees and rule-based models. It...
RPMM
RPMM is a sophisticated machine learning software utilizing a Recursively Partitioned Mixture Model to analyze Beta and Gaussian mixtures. It...
Rmalschains
Rmalschains implements memetic algorithms with local search chains, enhancing continuous optimization through a hybrid approach that combines genetic algorithms and...
bst: Gradient Boosting
The bst package implements a functional gradient descent algorithm tailored for various convex and non-convex loss functions, addressing both classical...
The Libra Toolkit
The Libra Toolkit comprises a suite of algorithms designed for learning and inference in discrete probabilistic models, such as Bayesian...
FRBS
FRBS is a robust implementation of various learning algorithms tailored for classification and regression tasks using fuzzy rule-based systems. It...
DEAP
DEAP serves as a groundbreaking evolutionary computation framework designed for swift prototyping and validation of innovative ideas. By emphasizing explicit...
RGP
The 'rgp' package is a specialized machine learning software designed for genetic programming. Although it has been archived since January...
OpenAI Gym
OpenAI Gym has been developed as an advanced technological toolkit that toolkit which is used for the development and for...
CORElearn
CORElearn offers a robust suite of C++ machine learning algorithms integrated with R, facilitating various classification and regression techniques. It...
Stanford Classifier
The Stanford Classifier is a Java-based maximum entropy classifier designed for categorizing data into multiple classes. It excels with text...
Company Information
- Company: R Project
- Country: Austria
