fix: Add more unit tests and fixes for consistency for CrossValidate

sygops · Nov 30, 2018 · 52d137e · 52d137e
1 parent 7489388
commit 52d137e
Show file tree

Hide file tree

Showing 15 changed files with 1,395 additions and 575 deletions.
diff --git a/browser.js b/browser.js
diff --git a/browser.min.js b/browser.min.js
diff --git a/dist/cross-validate.js b/dist/cross-validate.js
diff --git a/dist/cross-validate.js.map b/dist/cross-validate.js.map
diff --git a/dist/neural-network-gpu.js.map b/dist/neural-network-gpu.js.map
diff --git a/dist/neural-network.js b/dist/neural-network.js
diff --git a/dist/neural-network.js.map b/dist/neural-network.js.map
diff --git a/dist/recurrent/rnn-time-step.js b/dist/recurrent/rnn-time-step.js
diff --git a/dist/recurrent/rnn-time-step.js.map b/dist/recurrent/rnn-time-step.js.map
diff --git a/index.d.ts b/index.d.ts
@@ -3,6 +3,7 @@ export interface INeuralNetworkOptions {
   binaryThresh?: number;
   hiddenLayers?: number[];
   activation?: NeuralNetworkActivation;
+  leakyReluAlpha?: number;
 }
 
 export type NeuralNetworkActivation = 'sigmoid' | 'relu' | 'leaky-relu' | 'tanh';
@@ -47,8 +48,19 @@ export interface INeuralNetworkTrainingData {
 export type NeuralNetworkInput = number[];
 
 export interface INeuralNetworkTestResult {
-  misclasses: any,
-  error: number
+  misclasses: any;
+  error: number;
+  total: number;
+}
+
+export interface INeuralNetworkBinaryTestResult extends INeuralNetworkTestResult {
+  trueNeg: number;
+  truePos: number;
+  falseNeg: number;
+  falsePos: number;
+  precision: number;
+  recall: number;
+  accuracy: number;
 }
 
 export class NeuralNetwork {
@@ -57,7 +69,7 @@ export class NeuralNetwork {
   public train<T>(data: T, options?: INeuralNetworkTrainingOptions): INeuralNetworkState;
   public trainAsync(data: INeuralNetworkTrainingData, options?: INeuralNetworkTrainingOptions): Promise<INeuralNetworkState>;
   public trainAsync<T>(data: T, options?: INeuralNetworkTrainingOptions): Promise<INeuralNetworkState>;
-  public test(data: INeuralNetworkTrainingData): INeuralNetworkTestResult;
+  public test(data: INeuralNetworkTrainingData): INeuralNetworkTestResult | INeuralNetworkBinaryTestResult;
   public run(data: NeuralNetworkInput): NeuralNetworkInput;
   public run<T>(data: NeuralNetworkInput): T;
   public run<TInput, TOutput>(data: TInput): TOutput;