Learning Data Mining with R - Bater Makhabel [2015, PDF, ENG] Code
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Learning Data Mining with R - Bater Makhabel [2015, PDF, ENG] Code
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Torrent File Content (136 files)
Bater Makhabel - Learning Data Mining with R - 2015
Bater Makhabel - Learning Data Mining with R - 2015.pdf -
Bater Makhabel - Learning Data Mining with R - 2015.pdf -
6.98 MB
Code
chapter10/ch_10_ngram_classifier.R -
chapter10/ch_10_ngram_classifier.R -
269 bytes
chapter10/data/datasets003.csv -
321 bytes
chapter1/ch_01_sna1.R -
66 bytes
chapter1/ch_01_sna2.R -
70 bytes
chapter2/ch_02_apriori.R -
2.24 KB
chapter2/ch_02_association_rule.R -
161 bytes
chapter2/ch_02_eclat.R -
1.66 KB
chapter2/ch_02_fpgrowth.R -
5.58 KB
chapter2/ch_02_genmax.R -
2.14 KB
chapter2/ch_02_spade.R -
211 bytes
chapter2/data/datasets006.RData -
3.02 MB
chapter2/data/itemsets001.csv -
90 bytes
chapter2/data/itemsets002.csv -
90 bytes
chapter2/data/itemsets003.csv -
60 bytes
chapter2/data/itemsets005.csv -
60 bytes
chapter3/ch_03_cart.R -
484 bytes
chapter3/ch_03_naive_bayes_classifier.R -
1.57 KB
chapter3/data/datasets001.csv -
50.71 KB
chapter3/data/datasets002.csv -
0 bytes
chapter3/data/datasets003.csv -
1.4 KB
chapter3/data/datasets006.csv -
145 bytes
chapter4/ch_04_bp.R -
2.48 KB
chapter4/ch_04_knn.R -
1.69 KB
chapter4/ch_04_svm.R -
1.64 KB
chapter4/data/datasets011.csv -
1.45 KB
chapter4/data/itemsets005.csv -
3.93 KB
chapter5/chapter5/ch_05_ahclustering.R -
299 bytes
chapter5/chapter5/ch_05_clara.R -
934 bytes
chapter5/chapter5/ch_05_kmeans.R -
348 bytes
chapter5/chapter5/ch_05_kmedoids.R -
447 bytes
chapter5/chapter5/data/datasets001.csv -
0 bytes
chapter5/chapter5/data/datasets004.csv -
2.26 KB
chapter5/chapter5/data/datasets005.csv -
16.73 KB
chapter5/chapter5/data/datasets006.csv -
53.22 KB
chapter5/chapter5/data/datasets009.csv -
2.26 KB
chapter6/chapter6/ch_06_scan.R -
221 bytes
chapter6/chapter6/data/datasets001.csv -
19.99 KB
Learning Data Mining with R_Code_part 2/Chapter 3/ch_03_cart.r -
496 bytes
Learning Data Mining with R_Code_part 2/Chapter 4/ch_03_cart.r -
496 bytes
Learning Data Mining with R_Code_part 2/Chapter 4/ch_04_adaboost.R -
500 bytes
Learning Data Mining with R_Code_part 2/Chapter 4/ch_04_bagging.R -
499 bytes
Learning Data Mining with R_Code_part 2/Chapter 4/ch_04_bnn.R -
504 bytes
Learning Data Mining with R_Code_part 2/Chapter 4/ch_04_cba.R -
503 bytes
Learning Data Mining with R_Code_part 2/Chapter 4/ch_04_forestrc.R -
506 bytes
Learning Data Mining with R_Code_part 2/Chapter 4/ch_04_forestri.R -
506 bytes
Learning Data Mining with R_Code_part 2/Chapter 4/ch_04_svm.R -
503 bytes
Learning Data Mining with R_Code_part 2/Chapter 5/ch_03_cart.r -
496 bytes
Learning Data Mining with R_Code_part 2/Chapter 5/ch_04_adaboost.R -
500 bytes
Learning Data Mining with R_Code_part 2/Chapter 5/ch_04_bagging.R -
499 bytes
Description
Book Samples On Below URLs. Please Give Your Likes and Reviews
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Being able to deal with the array of problems that you may encounter during complex statistical projects can be difficult. If you have only a basic knowledge of R, this book will provide you with the skills and knowledge to successfully create and customize the most popular data mining algorithms to overcome these difficulties.
You will learn how to manipulate data with R using code snippets and be introduced to mining frequent patterns, association, and correlations while working with R programs. Discover how to write code for various predication models, stream data, and time-series data. You will also be introduced to solutions written in R based on RHadoop projects. You will finish this book feeling confident in your ability to know which data mining algorithm to apply in any situation.
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