Evaluation (deeplearning4j-core 0.0.3.3.3.alpha1 API)

java.lang.Object
- org.deeplearning4j.eval.Evaluation

```
public class Evaluation
extends Object
```
Evaluation metrics: precision, recall, f1

Author:

Adam Gibson

Constructor Summary

Constructors
Constructor and Description

Evaluation()

Constructors
Constructor and Description
`Evaluation()`

Method Summary

All Methods Instance Methods Concrete Methods
Modifier and Type	Method and Description
`double`	`accuracy()` Accuracy: TP + TN / (P + N)
`void`	`addToConfusion(int real, int guess)` Adds to the confusion matrix
`int`	`classCount(int i)` Returns the number of times the given label has actually occurred
`void`	`eval(org.nd4j.linalg.api.ndarray.INDArray realOutcomes, org.nd4j.linalg.api.ndarray.INDArray guesses)` Collects statistics on the real outcomes vs the guesses.
`double`	`f1()` TP: true positive FP: False Positive FN: False Negative F1 score: 2 * TP / (2TP + FP + FN)
`double`	`f1(int i)` Calculate f1 score for a given class
`double`	`falsePositive()` False positive: wrong guess
`void`	`incrementFalseNegatives(int i)`
`void`	`incrementFalsePositives(int i)`
`void`	`incrementTruePositives(int i)`
`double`	`negative()` Total negatives true negatives + falseNegatives
`int`	`numtimesPredicted(int label)` Returns the number of times a given label was predicted
`int`	`numTimesPredicted(int actual, int predicted)` Gets the number of times the given class was predicted for the given predicted label
`double`	`positive()` Returns all of the positive guesses: true positive + false negative
`double`	`precision()` Total precision based on guesses so far
`double`	`precision(int i)` Returns the precision for a given label
`double`	`recall()` Returns the recall for the outcomes
`double`	`recall(int i)`
`String`	`stats()`
`double`	`trueNegatives()` True negatives: correctly rejected

Methods inherited from class java.lang.Object
clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

- Constructor Detail
  - Evaluation
```
public Evaluation()
```
- Method Detail
  - eval
```
public void eval(org.nd4j.linalg.api.ndarray.INDArray realOutcomes,
                 org.nd4j.linalg.api.ndarray.INDArray guesses)
```
    Collects statistics on the real outcomes vs the guesses. This is for logistic outcome matrices such that the Note that an IllegalArgumentException is thrown if the two passed in matrices aren't the same length.
    
    Parameters:
    
    realOutcomes - the real outcomes (usually binary)
    
    guesses - the guesses (usually a probability vector)
  - stats
```
public String stats()
```
  - addToConfusion
```
public void addToConfusion(int real,
                           int guess)
```
    Adds to the confusion matrix
    
    Parameters:
    
    real - the actual guess
    
    guess - the system guess
  - classCount
```
public int classCount(int i)
```
    Returns the number of times the given label has actually occurred
    
    Parameters:
    
    i - the label
    
    Returns:
    
    the number of times the label actually occurred
  - numtimesPredicted
```
public int numtimesPredicted(int label)
```
    Returns the number of times a given label was predicted
    
    Parameters:
    
    label - the label to getFromOrigin
    
    Returns:
    
    the number of times the given label was predicted
  - numTimesPredicted
```
public int numTimesPredicted(int actual,
                             int predicted)
```
    Gets the number of times the given class was predicted for the given predicted label
    
    Parameters:
    
    actual - actual outcome
    
    predicted - predicted outcome
    
    Returns:
    
    number of time predicted
  - precision
```
public double precision()
```
    Total precision based on guesses so far
    
    Returns:
    
    the total precision based on guesses so far
  - trueNegatives
```
public double trueNegatives()
```
    True negatives: correctly rejected
    
    Returns:
    
    the total true negatives so far
  - falsePositive
```
public double falsePositive()
```
    False positive: wrong guess
    
    Returns:
    
    the count of the false positives
  - negative
```
public double negative()
```
    Total negatives true negatives + falseNegatives
    
    Returns:
    
    the overall negative count
  - positive
```
public double positive()
```
    Returns all of the positive guesses: true positive + false negative
    
    Returns:
  - accuracy
```
public double accuracy()
```
    Accuracy: TP + TN / (P + N)
    
    Returns:
    
    the accuracy of the guesses so far
  - f1
```
public double f1()
```
    TP: true positive FP: False Positive FN: False Negative F1 score: 2 * TP / (2TP + FP + FN)
    
    Returns:
    
    the f1 score or harmonic mean based on current guesses
  - f1
```
public double f1(int i)
```
    Calculate f1 score for a given class
    
    Parameters:
    
    i - the label to calculate f1 for
    
    Returns:
    
    the f1 score for the given label
  - recall
```
public double recall()
```
    Returns the recall for the outcomes
    
    Returns:
    
    the recall for the outcomes
  - recall
```
public double recall(int i)
```
  - precision
```
public double precision(int i)
```
    Returns the precision for a given label
    
    Parameters:
    
    i - the label
    
    Returns:
    
    the precision for the label
  - incrementTruePositives
```
public void incrementTruePositives(int i)
```
  - incrementFalseNegatives
```
public void incrementFalseNegatives(int i)
```
  - incrementFalsePositives
```
public void incrementFalsePositives(int i)
```

Class Evaluation

Constructor Summary

Method Summary

Methods inherited from class java.lang.Object

Constructor Detail

Evaluation

Method Detail

eval

stats

addToConfusion

classCount

numtimesPredicted

numTimesPredicted

precision

trueNegatives

falsePositive

negative

positive

accuracy

f1

f1

recall

recall

precision

incrementTruePositives

incrementFalseNegatives

incrementFalsePositives