machine-learning.data-sets: adding the linnerud dataset.
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! Copyright (C) 2012 John Benediktsson
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! See http://factorcode.org/license.txt for BSD license
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USING: assocs csv io.encodings.utf8 io.files kernel math.parser
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sequences ;
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USING: accessors ascii assocs csv io.encodings.utf8 io.files
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kernel math.parser sequences splitting ;
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IN: machine-learning.data-sets
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@ -17,6 +17,11 @@ C: <data-set> data-set
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"resource:extra/machine-learning/data-sets/" prepend
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utf8 file-contents ;
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: load-table ( name -- data names )
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load-file [ blank? ] trim string-lines
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[ [ blank? ] split-when ] map unclip
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[ [ [ string>number ] map ] map ] dip ;
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PRIVATE>
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: load-iris ( -- data-set )
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@ -32,3 +37,12 @@ PRIVATE>
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"sepal length (cm)" "sepal width (cm)"
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"petal length (cm)" "petal width (cm)"
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} <data-set> ;
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: load-linnerud ( -- data-set )
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data-set new
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"linnerud_exercise.csv" load-table
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[ >>data ] [ >>feature-names ] bi*
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"linnerud_physiological.csv" load-table
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[ >>target ] [ >>target-names ] bi*
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"linnerud.rst" load-file >>description ;
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Linnerrud dataset
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Notes
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-----
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Data Set Characteristics:
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:Number of Instances: 20
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:Number of Attributes: 3
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:Missing Attribute Values: None
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The Linnerud dataset constains two small dataset:
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- *exercise*: A list containing the following components: exercise data with
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20 observations on 3 exercise variables: Weight, Waist and Pulse.
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- *physiological*: Data frame with 20 observations on 3 physiological variables:
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Chins, Situps and Jumps.
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References
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----------
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* http://rgm2.lab.nig.ac.jp/RGM2/func.php?rd_id=mixOmics:linnerud
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* Tenenhaus, M. (1998). La regression PLS: theorie et pratique. Paris: Editions Technic.
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@ -0,0 +1,21 @@
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Chins Situps Jumps
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5 162 60
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2 110 60
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12 101 101
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12 105 37
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13 155 58
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4 101 42
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8 101 38
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6 125 40
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15 200 40
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17 251 250
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17 120 38
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13 210 115
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14 215 105
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1 50 50
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6 70 31
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12 210 120
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4 60 25
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11 230 80
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15 225 73
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2 110 43
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@ -0,0 +1,21 @@
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Weight Waist Pulse
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191 36 50
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189 37 52
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193 38 58
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162 35 62
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189 35 46
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182 36 56
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211 38 56
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167 34 60
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176 31 74
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154 33 56
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169 34 50
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166 33 52
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154 34 64
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247 46 50
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193 36 46
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202 37 62
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176 37 54
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157 32 52
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156 33 54
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138 33 68
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