accuracy-meter - npm Package Compare versions

Comparing version 1.1.1 to 1.1.2

accuracy-meter.js

@@ -0,44 +1,78 @@
+var Table = require('cli-table');
 
 
-var AccuracyMeter=module.exports=function AccuracyMeter(){
-    this.numberOfFalsePositive=0;
-    this.numberOfFalseNegative=0;
-    this.numberOfTruePositive=0;
+
+var AccuracyMeter = module.exports = function AccuracyMeter() {
+  this.numberOfFalsePositives = 0;
+  this.numberOfFalseNegatives = 0;
+  this.numberOfTruePositives = 0;
 }
 
-AccuracyMeter.prototype.add=function(predicted, golden){
-    var numberOfTruePositives;
-    var numberOfFalseNegatives;
-    var numberOfFalsePositives;
+AccuracyMeter.prototype.add = function(predicted, golden) {
+  var numberOfTruePositives;
+  var numberOfFalseNegatives;
+  var numberOfFalsePositives;
 
-    if (!Array.isArray(predicted) || !Array.isArray(golden)){
-        throw new Error('Please pass to add() function 2 arrays: predicted labels and golden labels');
-    }
+  if (!Array.isArray(predicted) || !Array.isArray(golden)) {
+    throw new Error('Please pass to add() function 2 arrays: predicted labels and golden labels');
+  }
 
-    numberOfTruePositives=predicted.filter(function(pred){
-        return golden.indexOf(pred)>=0;
+  numberOfTruePositives = predicted.filter(function(pred) {
+    return golden.indexOf(pred) >= 0;
+  }).length;
+  numberOfFalseNegatives = golden.filter(function(gold) {
+    return predicted.indexOf(gold) < 0;
+  }).length;
+  numberOfFalsePositives = predicted.filter(function(pred) {
+    return golden.indexOf(pred) < 0;
+  }).length;
+
+  this.numberOfFalsePositives = this.numberOfFalsePositives + numberOfFalsePositives;
+  this.numberOfTruePositives = this.numberOfTruePositives + numberOfTruePositives;
+  this.numberOfFalseNegatives = this.numberOfFalseNegatives + numberOfFalseNegatives;
+
+
+};
+
+AccuracyMeter.prototype.getResultToStringMethod = function(precision, recall, fscore) {
+
+  return function() {
+    var table = new Table({
+      head: ['Precision', 'Recall', 'Fscore'],
+      colWidths: [100, 200]
     });
-    numberOfFalseNegatives=golden.filter(function(gold){
-        return predicted.indexOf(gold)<0;
-    });
-    numberOfFalsePositives=predicted.filter(function(pred){
-        return golden.indexOf(pred)<0;
-    });
 
-    this.numberOfFalsePositive=this.numberOfFalsePositive+numberOfFalsePositives;
-    this.numberOfTruePositives=this.numberOfTruePositives+numberOfTruePositives;
-    this.numberOfFalseNegatives=this.numberOfFalseNegatives+numberOfFalseNegatives;
+    table.push([precision, recall, fscore]);
 
-    
+    return table.toString();
+
+  };
+
+
 };
 
-AccuracyMeter.prototype.print=function(){
-    
-    var precision;
-    var recall;
-    var fmesasure;
+AccuracyMeter.prototype.get = function() {
+  var precision;
+  var recall;
+  var fscore;
 
-    
-    
+  precision = this.numberOfTruePositives / (this.numberOfTruePositives + this.numberOfFalsePositives);
+  recall = this.numberOfTruePositives / (this.numberOfTruePositives + this.numberOfFalseNegatives);
+
+  fscore = 2 * (precision * recall) / (precision + recall);
+
+  return {
+    precision: precision,
+    recall: recall,
+    fscore: fscore,
+    toString: this.getResultToStringMethod(precision, recall, fscore)
+  };
 };
+AccuracyMeter.prototype.print = function() {
 
+  console.log(this.get().toString());
+
+
+
+};
+

package.json

 {
   "name": "accuracy-meter",
-  "version": "1.1.1",
+  "version": "1.1.2",
   "description": "",
   "main": "accuracy-meter.js",
   "scripts": {
-    "test": "echo \"Error: no test specified\" && exit 1"
+    "test": "cd test && mocha ./test.js"
   },
   "author": "",
-  "license": "ISC"
+  "license": "ISC",
+  "dependencies": {
+    "cli-table": "^0.3.1"
+  },
+  "devDependencies": {
+    "chai": "^3.5.0"
+  }
 }

README.md

@@ -21,1 +21,23 @@ # accuracy-meter
 ```
+
+## API
+
+### add(predicted, golden)
+
+It adds a pair <predicted, golden>, representing the set of prdicted labels and the set of golden labels. Golden and predicted labels are both arrays.
+
+### get()
+
+It returns an object containing:
+* precision
+* recall
+* fscore
+
+# Why
+
+* node.js is not a standard language for NLP tasks, but...
+* machine learning is more and more in the cloud (check Watson NLP Classifier)
+* machine learning is becoming just a set of Http end points to invoke
+* node.js is perfect as middleware and client among Http end points
+* ...accuracy-meter might help you to measure the accuracy of your algorithms in the cloud
+

Fixed alerts

No tests

Quality

Package does not have any tests. This is a strong signal of a poorly maintained or low quality package.

Found 1 instance in 1 package

Improved metrics

Total package byte prevSize

3802

increased by127.53%

Number of package files

4

increased by33.33%

Lines of code

74

increased by146.67%

Number of low quality alerts

1

decreased by-50%

Number of lines in readme file

43

increased by104.76%

Worsened metrics

Dependency count

1

increased byInfinity%

Dev dependency count

1

increased byInfinity%

Dependency changes

• + Addedcli-table@^0.3.1

• + Addedcli-table@0.3.11(transitive)

• + Addedcolors@1.0.3(transitive)