In seymakalay/pomodoro: Predictive Power of Linear and Tree Modeling

knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>",
  fig.path = "man/figures/README-",
  out.width = "100%"
)

<!-- # pomodoro

library(usethis) use_logo("img.png", geometry = "240x278", retina = TRUE)

library(hexSticker) library(UCSCXenaTools)

sticker("img.png", package="UCSCXenaTools", p_size=4.5, s_x=0.9, s_y=1, s_width=1.7, s_height=1.3, + p_x = 1.1, p_y = 0.9, + url = "https://cran.r-project.org/package=UCSCXenaTools", u_color = "white", u_size = 1, + h_fill="black", h_color="grey", + filename="man/figures/logo3.png") -->

pomodoro

The goal of pomodoro is to provide functions to make predictive modeling easy.

Installation

You can install the released version of pomodoro from CRAN with:

install.packages("pomodoro")
library(pomodoro)

Overview

Runs bagging, boosting, random forest, multinominal logistic and logistic models. The purpose of this package is to report the predictive modelling results with ease.

seymakalay/pomodoro documentation built on May 23, 2022, 3:25 p.m.