عنوان
پدید آورنده
موضوع
رده
QA276.45.R3 .T388 2018
QA276
.
45
.
R3
.
T388
2018
کتابخانه
محل استقرار
شابک
شابک
1788624149
شابک
1788629175
شابک
9781788624145
شابک
9781788629171
عنوان و نام پديدآور
عنوان اصلي
Hands-On Ensemble Learning with R :
نام عام مواد
[Book]
ساير اطلاعات عنواني
a Beginner's Guide to Combining the Power of Machine Learning Algorithms Using Ensemble Techniques.
وضعیت نشر و پخش و غیره
محل نشرو پخش و غیره
Birmingham :
نام ناشر، پخش کننده و غيره
Packt Publishing Ltd,
تاریخ نشرو بخش و غیره
2018.
مشخصات ظاهری
نام خاص و کميت اثر
1 online resource (376 pages)
يادداشت کلی
متن يادداشت
Regression models.
یادداشتهای مربوط به مندرجات
متن يادداشت
Cover; Copyright; Contributors; Table of Contents; Preface; Chapter 1: Introduction to Ensemble Techniques; Datasets; Hypothyroid; Waveform; German Credit; Iris; Pima Indians Diabetes; US Crime; Overseas visitors; Primary Biliary Cirrhosis; Multishapes; Board Stiffness; Statistical/machine learning models; Logistic regression model; Logistic regression for hypothyroid classification; Neural networks; Neural network for hypothyroid classification; Naïve Bayes classifier; Naïve Bayes for hypothyroid classification; Decision tree; Decision tree for hypothyroid classification.
متن يادداشت
Bootstrapping survival models*Bootstrapping time series models*; Summary; Chapter 3: Bagging; Technical requirements; Classification trees and pruning; Bagging; k-NN classifier; Analyzing waveform data; k-NN bagging; Summary; Chapter 4: Random Forests; Technical requirements; Random Forests; Variable importance; Proximity plots; Random Forest nuances; Comparisons with bagging; Missing data imputation; Clustering with Random Forest; Summary; Chapter 5: The Bare Bones Boosting Algorithms; Technical requirements; The general boosting algorithm; Adaptive boosting; Gradient boosting.
متن يادداشت
Building it from scratchSquared-error loss function; Using the adabag and gbm packages; Variable importance; Comparing bagging, random forests, and boosting; Summary; Chapter 6: Boosting Refinements; Technical requirements; Why does boosting work?; The gbm package; Boosting for count data; Boosting for survival data; The xgboost package; The h2o package; Summary; Chapter 7: The General Ensemble Technique; Technical requirements; Why does ensembling work?; Ensembling by voting; Majority voting; Weighted voting; Ensembling by averaging; Simple averaging; Weight averaging; Stack ensembling.
متن يادداشت
Support vector machinesSVM for hypothyroid classification; The right model dilemma!; An ensemble purview; Complementary statistical tests; Permutation test; Chi-square and McNemar test; ROC test; Summary; Chapter 2: Bootstrapping; Technical requirements; The jackknife technique; The jackknife method for mean and variance; Pseudovalues method for survival data; Bootstrap -- a statistical method; The standard error of correlation coefficient; The parametric bootstrap; Eigen values; Rule of thumb; The boot package; Bootstrap and testing hypotheses; Bootstrapping regression models.
بدون عنوان
0
بدون عنوان
8
بدون عنوان
8
بدون عنوان
8
یادداشتهای مربوط به خلاصه یا چکیده
متن يادداشت
Chapter 8: Ensemble Diagnostics; Technical requirements; What is ensemble diagnostics?; Ensemble diversity; Numeric prediction; Class prediction; Pairwise measure; Disagreement measure; Yule's or Q-statistic; Correlation coefficient measure; Cohen's statistic; Double-fault measure; Interrating agreement; Entropy measure; Kohavi-Wolpert measure; Disagreement measure for ensemble; Measurement of interrater agreement; Summary; Chapter 9: Ensembling Regression Models; Technical requirements; Pre-processing the housing data; Visualization and variable reduction; Variable clustering.
متن يادداشت
This book introduces you to the concept of ensemble learning and demonstrates how different machine learning algorithms can be combined to build efficient machine learning models. Use R to implement the popular trilogy of ensemble techniques, i.e. bagging, random forest and boosting, to build faster and more accurate machine learning models.
یادداشتهای مربوط به سفارشات
منبع سفارش / آدرس اشتراک
01201872
شماره انبار
B09012
ویراست دیگر از اثر در قالب دیگر رسانه
عنوان
Hands-On Ensemble Learning with R : A Beginner's Guide to Combining the Power of Machine Learning Algorithms Using Ensemble Techniques.
شماره استاندارد بين المللي کتاب و موسيقي
9781788624145
موضوع (اسم عام یاعبارت اسمی عام)
موضوع مستند نشده
Computer algorithms.
موضوع مستند نشده
Machine learning.
موضوع مستند نشده
R.
موضوع مستند نشده
Computer algorithms.
موضوع مستند نشده
Machine learning.
رده بندی ديویی
شماره
519
.
502855133
ويراست
23
رده بندی کنگره
شماره رده
QA276
.
45
.
R3
نشانه اثر
.
T388
2018
نام شخص به منزله سر شناسه - (مسئولیت معنوی درجه اول )
مستند نام اشخاص تاييد نشده
Tattar, Prabhanjan Narayanachar.
مبدا اصلی
تاريخ عمليات
20200823060423.0
قواعد فهرست نويسي ( بخش توصيفي )
pn
دسترسی و محل الکترونیکی
نام الکترونيکي
مطالعه متن کتاب اطلاعات رکورد کتابشناسی
نوع ماده
[Book]
اطلاعات دسترسی رکورد
تكميل شده
Y
