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softmax function implementation in js
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// Fork & examples for the one-line version by @vladimir-ivanov: | |
//let softmax = (arr) => (index) => Math.exp(arr[index]) / arr.map(y => Math.exp(y)).reduce((a, b) => a + b); | |
// | |
// Also see comments for improvements | |
function softmax(arr) { | |
return arr.map(function(value,index) { | |
return Math.exp(value) / arr.map( function(y /*value*/){ return Math.exp(y) } ).reduce( function(a,b){ return a+b }) | |
}) | |
} | |
example1=[ 0.9780449271202087, | |
0.01590355671942234, | |
0.0019390975357964635, | |
0.0015482910675927997, | |
0.0012942816829308867, | |
0.0006004497990943491, | |
0.0004827099328394979, | |
0.0001868270628619939 ] | |
softmax1=softmax(example1) | |
example2= [ | |
{ prob: 0.32289665937423706, cat: '25_32' }, | |
{ prob: 0.15404804050922394, cat: '38_43' }, | |
{ prob: 0.03673655539751053, cat: '4_6' }, | |
{ prob: 0.01545996405184269, cat: '48_53' }, | |
{ prob: 0.011709162034094334, cat: '15_20' }, | |
{ prob: 0.008010754361748695, cat: '8_13' }, | |
{ last: true, prob: 0.0054732030257582664, cat: '60+' } ].map(function(v){return v.prob}) | |
softmax2=softmax(example2) | |
example3=[ { prob: 0.125, cat: '25_32' }, | |
{ prob: 0.125, cat: '38_43' }, | |
{ prob: 0.125, cat: '15_20' }, | |
{ prob: 0.125, cat: '8_13' }, | |
{ prob: 0.125, cat: '4_6' }, | |
{ prob: 0.125, cat: '48_53' }, | |
{ prob: 0.125, cat: '60+' }, | |
{ prob: 0.125, cat: '0_2' } ].map(function(v){return v.prob}) | |
softmax3=softmax(example3) |
By any chance, does anyone have an example of the softmax derivative ? Or is able to tell me if this one is correct:
function derivative(arr) {
const values = softmax(arr);
return arr.map((x, i) => {
return values[i] * (values[i] - (i === 0 ? 1 : 0));
});
}
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More efficient version.
Math.max(...arr)
which will causeRangeError: Maximum call stack size exceeded
If you still want to use prettier version you could just replace
Math.max(...arr)
withreduce
.