Data Scientist 1 @ AstranaHealth
//Credit to: https://gist.github.com/stephband/8237123
function Viterbi(data) {
var V = [{}]; //V acts as the "alpha"
var path = {};
// Initialize base cases (t == 0)
for(var i=0;i<data.states.length;i++) {
var state = data.states[i];
V[0][state] = data.start_probability[state] * data.emission_probability[state][data.observations[0]];
path[state] = [state]; //Backpointer
}
// Run Viterbi for t > 0
for(var t=1;t<data.observations.length;t++) {
V.push({}); //Push adds new item to array
var newpath = {};
//For each state
for(var i=0;i<data.states.length;i++) {
var state = data.states[i];
var max = [0,null];
for(var j=0;j<data.states.length;j++) {
var state0 = data.states[j];
// Calculate the probablity
var calc = V[t-1][state0]
* data.transition_probability[state0][state]
* data.emission_probability[state][data.observations[t]];
if(calc > max[0])
max = [calc,state0];
}
V[t][state] = max[0];
newpath[state] = path[max[1]].concat(state);
/*
Backpointer
max[1] = [state0]
concat combines two arrays together, yielding a new array with [state0,state]
Recall that we only need to know the store the maximum of the previous hidden state for each one of the
two current hidden states
*/
}
path = newpath;
}
var max = [0,null];
for(var i=0;i<data.states.length;i++) {
var state = data.states[i];
var calc = V[data.observations.length-1][state];
if(calc > max[0]) max = [calc,state];
}
return [max[0], path[max[1]]];
}
result = Viterbi({
states: [
'Low',
'High'
],
observations: [
'Rain',
'Dry'
],
start_probability: {
'Low': 0.4,
'High': 0.6
},
transition_probability: {
'Low' : {'Low': 0.3, 'High': 0.7},
'High' : {'High': 0.8, 'Low': 0.2}
},
emission_probability: {
'Low' : {'Rain': 0.6, 'Dry': 0.4},
'High' : {'Rain': 0.4, 'Dry': 0.6}
}
});
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