LocalDeepnet.prototype.predictList = function (inputArray) {
/**
* Computes the prediction with a list of networks.
*
* @param {array} inputArray Input data array prepared according to
* the input fields description.
*/
var inputArrayTrees, youts, model, index, len;
if (typeof this.network.trees !== 'undefined' && this.network.trees != null) {
inputArrayTrees = pp.treeTransform(inputArray, this.network.trees);
youts = [];
for (index = 0, len = this.networks.length; index < len; index++) {
model = this.networks[index];
if (typeof model.trees !== 'undefined' && model.trees != null
&& model.trees) {
// so far, model.tress = false when empty, but just in case
youts.push(this.modelPredict(inputArrayTrees, model));
} else {
youts.push(this.modelPredict(inputArray, model));
}
}
return this.toPrediction(net.sumAndNormalize(youts, this.regression));
}
}
LocalDeepnet.prototype.predictSingle = function (inputArray) {
/**
* Computes the prediction with a single network.
*
* @param {array} inputArray Input data array prepared according to
* the input fields description.
*/
if (typeof this.network.trees !== 'undefined' &&
this.network.trees) {
inputArray = pp.treeTransform(inputArray, this.network.trees);
}
return this.toPrediction(this.modelPredict(inputArray, this.network));
}