- Hands-On Ensemble Learning with R
- Prabhanjan Narayanachar Tattar
- 118字
- 2021-07-23 19:10:50
Pima Indians Diabetes
Diabetes is a health hazard, which is mostly incurable, and patients who are diagnosed with it have to adjust their lifestyles in order to cater to this condition. Based on variables such as pregnant
, glucose
, pressure
, triceps
, insulin
, mass
, pedigree
, and age
, the problem here is to classify the person as diabetic or not. Here, we have 768 observations. This dataset is drawn from the mlbench
package:
> data("PimaIndiansDiabetes") > set.seed(12345) > Train_Test <- sample(c("Train","Test"),nrow(PimaIndiansDiabetes),replace = TRUE, + prob = c(0.7,0.3)) > head(Train_Test) [1] "Test" "Test" "Test" "Test" "Train" "Train" > PimaIndiansDiabetes_Train <- PimaIndiansDiabetes[Train_Test=="Train",] > PimaIndiansDiabetes_TestX <- within(PimaIndiansDiabetes[Train_Test=="Test",], + rm(diabetes)) > PimaIndiansDiabetes_TestY <- PimaIndiansDiabetes[Train_Test=="Test","diabetes"] > PID_Formula <- as.formula("diabetes~.")
The five datasets described up to this point are classification problems. We look at one example each for regression, time series, survival, clustering, and outlier detection problems.
推薦閱讀
- 大學(xué)計(jì)算機(jī)基礎(chǔ):基礎(chǔ)理論篇
- 平面設(shè)計(jì)初步
- 走入IBM小型機(jī)世界
- 計(jì)算機(jī)原理
- 輕松學(xué)Java
- 群體智能與數(shù)據(jù)挖掘
- Maya 2012從入門到精通
- 數(shù)據(jù)庫原理與應(yīng)用技術(shù)
- Nginx高性能Web服務(wù)器詳解
- PVCBOT機(jī)器人控制技術(shù)入門
- 空間機(jī)械臂建模、規(guī)劃與控制
- Silverlight 2完美征程
- SQL Server數(shù)據(jù)庫應(yīng)用基礎(chǔ)(第2版)
- 計(jì)算機(jī)辦公應(yīng)用培訓(xùn)教程
- TensorFlow 2.0卷積神經(jīng)網(wǎng)絡(luò)實(shí)戰(zhàn)