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README.md

#Table of Contents



titanic.csv

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Source: http://lib.stat.cmu.edu/S/Harrell/data/descriptions/titanic.html

  • sample size: 1313
  • features: 10
Name Levels Storage NAs
pclass 3 integer 0
survived double 0
name character 0
age double 680
embarked 3 integer 492
home.dest 371 integer 559
room character 0
ticket character 0
boat 99 integer 966
sex 2 integer 0

These data were obtained from Robert Dawson, Saint Mary's University, E-mail. The variables are pclass, age, sex, survived. These data frames are useful for demonstrating many of the functions in Hmisc as well as demonstrating binary logistic regression analysis using the Design library. For more details and references see Simonoff, Jeffrey S (1997): The "unusual episode" and a second statistics course. J Statistics Education, Vol. 5 No. 1.




wine.csv

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Source: https://archive.ics.uci.edu/ml/datasets/Wine

Bache, K. & Lichman, M. (2013). UCI Machine Learning Repository. Irvine, CA: University of California, School of Information and Computer Science.

wine.csv.csv
Samples 178
Features 13
Classes 3
Data Set Characteristics: Multivariate
Attribute Characteristics: Integer, Real
Associated Tasks: Classification
Missing Values None
column attribute
1) Class Label
2) Alcohol
3) Malic acid
4) Ash
5) Alcalinity of ash
6) Magnesium
7) Total phenols
8) Flavanoids
9) Nonflavanoid phenols
10) Proanthocyanins
11) intensity
12) Hue
13) OD280/OD315 of diluted wines
14) Proline
class samples
1 59
2 71
3 48

Original Owners:

Forina, M. et al, PARVUS - An Extendible Package for Data Exploration, Classification and Correlation. Institute of Pharmaceutical and Food Analysis and Technologies, Via Brigata Salerno, 16147 Genoa, Italy.




iris.csv

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Source:https://archive.ics.uci.edu/ml/datasets/Iris

Bache, K. & Lichman, M. (2013). UCI Machine Learning Repository. Irvine, CA: University of California, School of Information and Computer Science.

iris.csv
Samples 150
Features 4
Classes 3
Data Set Characteristics: Multivariate
Attribute Characteristics: Real
Associated Tasks: Classification
Missing Values None
column attribute
1) sepal length in cm
2) sepal width in cm
3) petal length in cm
4) petal width in cm
5) class label
class samples
Iris-setosa 50
Iris-versicolor 50
Iris-virginica 50

Creator: R.A. Fisher (1936)