jam/test/test-ice3.js

1030 lines
16 KiB
JavaScript

var training_data = [
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"variety": "Versicolor"
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},
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"variety": "Versicolor"
},
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},
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},
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},
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"variety": "Versicolor"
},
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"variety": "Versicolor"
},
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},
{
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},
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"variety": "Virginica"
},
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},
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"variety": "Virginica"
},
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},
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},
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},
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"variety": "Virginica"
},
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"variety": "Virginica"
},
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"variety": "Virginica"
},
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"variety": "Virginica"
},
{
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"pwidth": 1.9,
"variety": "Virginica"
},
{
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"variety": "Virginica"
},
{
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"pwidth": 2.0,
"variety": "Virginica"
},
{
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"variety": "Virginica"
},
{
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"pwidth": 2.3,
"variety": "Virginica"
},
{
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"pwidth": 1.8,
"variety": "Virginica"
},
{
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"swidth": 3.8,
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"pwidth": 2.2,
"variety": "Virginica"
},
{
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"pwidth": 2.3,
"variety": "Virginica"
},
{
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"variety": "Virginica"
},
{
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"variety": "Virginica"
},
{
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"swidth": 2.8,
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"pwidth": 2.0,
"variety": "Virginica"
},
{
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"swidth": 2.8,
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"pwidth": 2.0,
"variety": "Virginica"
},
{
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"swidth": 2.7,
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"pwidth": 1.8,
"variety": "Virginica"
},
{
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"swidth": 3.3,
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"pwidth": 2.1,
"variety": "Virginica"
},
{
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"swidth": 3.2,
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"pwidth": 1.8,
"variety": "Virginica"
},
{
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"swidth": 2.8,
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"pwidth": 1.8,
"variety": "Virginica"
},
{
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"pwidth": 1.8,
"variety": "Virginica"
},
{
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"pwidth": 2.1,
"variety": "Virginica"
},
{
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"swidth": 3.0,
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"pwidth": 1.6,
"variety": "Virginica"
},
{
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"swidth": 2.8,
"plength": 6.1,
"pwidth": 1.9,
"variety": "Virginica"
},
{
"slength": 7.9,
"swidth": 3.8,
"plength": 6.4,
"pwidth": 2.0,
"variety": "Virginica"
},
{
"slength": 6.4,
"swidth": 2.8,
"plength": 5.6,
"pwidth": 2.2,
"variety": "Virginica"
},
{
"slength": 6.3,
"swidth": 2.8,
"plength": 5.1,
"pwidth": 1.5,
"variety": "Virginica"
},
{
"slength": 6.1,
"swidth": 2.6,
"plength": 5.6,
"pwidth": 1.4,
"variety": "Virginica"
},
{
"slength": 7.7,
"swidth": 3.0,
"plength": 6.1,
"pwidth": 2.3,
"variety": "Virginica"
},
{
"slength": 6.3,
"swidth": 3.4,
"plength": 5.6,
"pwidth": 2.4,
"variety": "Virginica"
},
{
"slength": 6.4,
"swidth": 3.1,
"plength": 5.5,
"pwidth": 1.8,
"variety": "Virginica"
},
{
"slength": 6.0,
"swidth": 3.0,
"plength": 4.8,
"pwidth": 1.8,
"variety": "Virginica"
},
{
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"swidth": 3.1,
"plength": 5.4,
"pwidth": 2.1,
"variety": "Virginica"
},
{
"slength": 6.7,
"swidth": 3.1,
"plength": 5.6,
"pwidth": 2.4,
"variety": "Virginica"
},
{
"slength": 6.9,
"swidth": 3.1,
"plength": 5.1,
"pwidth": 2.3,
"variety": "Virginica"
},
{
"slength": 5.8,
"swidth": 2.7,
"plength": 5.1,
"pwidth": 1.9,
"variety": "Virginica"
},
{
"slength": 6.8,
"swidth": 3.2,
"plength": 5.9,
"pwidth": 2.3,
"variety": "Virginica"
},
{
"slength": 6.7,
"swidth": 3.3,
"plength": 5.7,
"pwidth": 2.5,
"variety": "Virginica"
},
{
"slength": 6.7,
"swidth": 3.0,
"plength": 5.2,
"pwidth": 2.3,
"variety": "Virginica"
},
{
"slength": 6.3,
"swidth": 2.5,
"plength": 5.0,
"pwidth": 1.9,
"variety": "Virginica"
},
{
"slength": 6.5,
"swidth": 3.0,
"plength": 5.2,
"pwidth": 2.0,
"variety": "Virginica"
}
]
var target = "variety";
var features = ["slength", "swidth","plength","pwidth"];
var model = ml.learn({
algorithm:ml.ML.ICE,
data:training_data,
target:target,
features:features,
eps:0.1
})
print(ml.classify(model,training_data).map(function (row,index) {
row.y=training_data[index][target]
return row;
}))
print(ml.print(model).split('\n').length)