# Cloud AutoML V1 Client - Class ConfidenceMetricsEntry (2.1.3)

2.1.3 (latest) 2.1.2 2.0.5 1.6.5 1.5.4 1.4.17 Reference documentation and code samples for the Cloud AutoML V1 Client class ConfidenceMetricsEntry.

Metrics for a single confidence threshold.

Generated from protobuf message `google.cloud.automl.v1.ClassificationEvaluationMetrics.ConfidenceMetricsEntry`

## Namespace

Google \\ Cloud \\ AutoMl \\ V1 \\ ClassificationEvaluationMetrics

## Methods

### __construct

Constructor.

| **Parameters** ||
|---|---|
| **Name** | **Description** |
| `data` | `array` Optional. Data for populating the Message object. |
| `↳ confidence_threshold` | `float` Output only. Metrics are computed with an assumption that the model never returns predictions with score lower than this value. |
| `↳ position_threshold` | `int` Output only. Metrics are computed with an assumption that the model always returns at most this many predictions (ordered by their score, descendingly), but they all still need to meet the confidence_threshold. |
| `↳ recall` | `float` Output only. Recall (True Positive Rate) for the given confidence threshold. |
| `↳ precision` | `float` Output only. Precision for the given confidence threshold. |
| `↳ false_positive_rate` | `float` Output only. False Positive Rate for the given confidence threshold. |
| `↳ f1_score` | `float` Output only. The harmonic mean of recall and precision. |
| `↳ recall_at1` | `float` Output only. The Recall (True Positive Rate) when only considering the label that has the highest prediction score and not below the confidence threshold for each example. |
| `↳ precision_at1` | `float` Output only. The precision when only considering the label that has the highest prediction score and not below the confidence threshold for each example. |
| `↳ false_positive_rate_at1` | `float` Output only. The False Positive Rate when only considering the label that has the highest prediction score and not below the confidence threshold for each example. |
| `↳ f1_score_at1` | `float` Output only. The harmonic mean of [recall_at1](https://docs.cloud.google.com/php/docs/reference/cloud-automl/latest/V1.ClassificationEvaluationMetrics.ConfidenceMetricsEntry#_Google_Cloud_AutoMl_V1_ClassificationEvaluationMetrics_ConfidenceMetricsEntry__getRecallAt1__) and [precision_at1](https://docs.cloud.google.com/php/docs/reference/cloud-automl/latest/V1.ClassificationEvaluationMetrics.ConfidenceMetricsEntry#_Google_Cloud_AutoMl_V1_ClassificationEvaluationMetrics_ConfidenceMetricsEntry__getPrecisionAt1__). |
| `↳ true_positive_count` | `int|string` Output only. The number of model created labels that match a ground truth label. |
| `↳ false_positive_count` | `int|string` Output only. The number of model created labels that do not match a ground truth label. |
| `↳ false_negative_count` | `int|string` Output only. The number of ground truth labels that are not matched by a model created label. |
| `↳ true_negative_count` | `int|string` Output only. The number of labels that were not created by the model, but if they would, they would not match a ground truth label. |

### getConfidenceThreshold

Output only. Metrics are computed with an assumption that the model
never returns predictions with score lower than this value.

| **Returns** ||
|---|---|
| **Type** | **Description** |
| `float` |   |

### setConfidenceThreshold

Output only. Metrics are computed with an assumption that the model
never returns predictions with score lower than this value.

| **Parameter** ||
|---|---|
| **Name** | **Description** |
| `var` | `float` |

| **Returns** ||
|---|---|
| **Type** | **Description** |
| `$this` |   |

### getPositionThreshold

Output only. Metrics are computed with an assumption that the model
always returns at most this many predictions (ordered by their score,
descendingly), but they all still need to meet the confidence_threshold.

| **Returns** ||
|---|---|
| **Type** | **Description** |
| `int` |   |

### setPositionThreshold

Output only. Metrics are computed with an assumption that the model
always returns at most this many predictions (ordered by their score,
descendingly), but they all still need to meet the confidence_threshold.

| **Parameter** ||
|---|---|
| **Name** | **Description** |
| `var` | `int` |

| **Returns** ||
|---|---|
| **Type** | **Description** |
| `$this` |   |

### getRecall

Output only. Recall (True Positive Rate) for the given confidence
threshold.

| **Returns** ||
|---|---|
| **Type** | **Description** |
| `float` |   |

### setRecall

Output only. Recall (True Positive Rate) for the given confidence
threshold.

| **Parameter** ||
|---|---|
| **Name** | **Description** |
| `var` | `float` |

| **Returns** ||
|---|---|
| **Type** | **Description** |
| `$this` |   |

### getPrecision

Output only. Precision for the given confidence threshold.

| **Returns** ||
|---|---|
| **Type** | **Description** |
| `float` |   |

### setPrecision

Output only. Precision for the given confidence threshold.

| **Parameter** ||
|---|---|
| **Name** | **Description** |
| `var` | `float` |

| **Returns** ||
|---|---|
| **Type** | **Description** |
| `$this` |   |

### getFalsePositiveRate

Output only. False Positive Rate for the given confidence threshold.

| **Returns** ||
|---|---|
| **Type** | **Description** |
| `float` |   |

### setFalsePositiveRate

Output only. False Positive Rate for the given confidence threshold.

| **Parameter** ||
|---|---|
| **Name** | **Description** |
| `var` | `float` |

| **Returns** ||
|---|---|
| **Type** | **Description** |
| `$this` |   |

### getF1Score

Output only. The harmonic mean of recall and precision.

| **Returns** ||
|---|---|
| **Type** | **Description** |
| `float` |   |

### setF1Score

Output only. The harmonic mean of recall and precision.

| **Parameter** ||
|---|---|
| **Name** | **Description** |
| `var` | `float` |

| **Returns** ||
|---|---|
| **Type** | **Description** |
| `$this` |   |

### getRecallAt1

Output only. The Recall (True Positive Rate) when only considering the
label that has the highest prediction score and not below the confidence
threshold for each example.

| **Returns** ||
|---|---|
| **Type** | **Description** |
| `float` |   |

### setRecallAt1

Output only. The Recall (True Positive Rate) when only considering the
label that has the highest prediction score and not below the confidence
threshold for each example.

| **Parameter** ||
|---|---|
| **Name** | **Description** |
| `var` | `float` |

| **Returns** ||
|---|---|
| **Type** | **Description** |
| `$this` |   |

### getPrecisionAt1

Output only. The precision when only considering the label that has the
highest prediction score and not below the confidence threshold for each
example.

| **Returns** ||
|---|---|
| **Type** | **Description** |
| `float` |   |

### setPrecisionAt1

Output only. The precision when only considering the label that has the
highest prediction score and not below the confidence threshold for each
example.

| **Parameter** ||
|---|---|
| **Name** | **Description** |
| `var` | `float` |

| **Returns** ||
|---|---|
| **Type** | **Description** |
| `$this` |   |

### getFalsePositiveRateAt1

Output only. The False Positive Rate when only considering the label that
has the highest prediction score and not below the confidence threshold
for each example.

| **Returns** ||
|---|---|
| **Type** | **Description** |
| `float` |   |

### setFalsePositiveRateAt1

Output only. The False Positive Rate when only considering the label that
has the highest prediction score and not below the confidence threshold
for each example.

| **Parameter** ||
|---|---|
| **Name** | **Description** |
| `var` | `float` |

| **Returns** ||
|---|---|
| **Type** | **Description** |
| `$this` |   |

### getF1ScoreAt1

Output only. The harmonic mean of [recall_at1](https://docs.cloud.google.com/php/docs/reference/cloud-automl/latest/V1.ClassificationEvaluationMetrics.ConfidenceMetricsEntry#_Google_Cloud_AutoMl_V1_ClassificationEvaluationMetrics_ConfidenceMetricsEntry__getRecallAt1__) and [precision_at1](https://docs.cloud.google.com/php/docs/reference/cloud-automl/latest/V1.ClassificationEvaluationMetrics.ConfidenceMetricsEntry#_Google_Cloud_AutoMl_V1_ClassificationEvaluationMetrics_ConfidenceMetricsEntry__getPrecisionAt1__).

| **Returns** ||
|---|---|
| **Type** | **Description** |
| `float` |   |

### setF1ScoreAt1

Output only. The harmonic mean of [recall_at1](https://docs.cloud.google.com/php/docs/reference/cloud-automl/latest/V1.ClassificationEvaluationMetrics.ConfidenceMetricsEntry#_Google_Cloud_AutoMl_V1_ClassificationEvaluationMetrics_ConfidenceMetricsEntry__getRecallAt1__) and [precision_at1](https://docs.cloud.google.com/php/docs/reference/cloud-automl/latest/V1.ClassificationEvaluationMetrics.ConfidenceMetricsEntry#_Google_Cloud_AutoMl_V1_ClassificationEvaluationMetrics_ConfidenceMetricsEntry__getPrecisionAt1__).

| **Parameter** ||
|---|---|
| **Name** | **Description** |
| `var` | `float` |

| **Returns** ||
|---|---|
| **Type** | **Description** |
| `$this` |   |

### getTruePositiveCount

Output only. The number of model created labels that match a ground truth
label.

| **Returns** ||
|---|---|
| **Type** | **Description** |
| `int|string` |   |

### setTruePositiveCount

Output only. The number of model created labels that match a ground truth
label.

| **Parameter** ||
|---|---|
| **Name** | **Description** |
| `var` | `int|string` |

| **Returns** ||
|---|---|
| **Type** | **Description** |
| `$this` |   |

### getFalsePositiveCount

Output only. The number of model created labels that do not match a
ground truth label.

| **Returns** ||
|---|---|
| **Type** | **Description** |
| `int|string` |   |

### setFalsePositiveCount

Output only. The number of model created labels that do not match a
ground truth label.

| **Parameter** ||
|---|---|
| **Name** | **Description** |
| `var` | `int|string` |

| **Returns** ||
|---|---|
| **Type** | **Description** |
| `$this` |   |

### getFalseNegativeCount

Output only. The number of ground truth labels that are not matched
by a model created label.

| **Returns** ||
|---|---|
| **Type** | **Description** |
| `int|string` |   |

### setFalseNegativeCount

Output only. The number of ground truth labels that are not matched
by a model created label.

| **Parameter** ||
|---|---|
| **Name** | **Description** |
| `var` | `int|string` |

| **Returns** ||
|---|---|
| **Type** | **Description** |
| `$this` |   |

### getTrueNegativeCount

Output only. The number of labels that were not created by the model,
but if they would, they would not match a ground truth label.

| **Returns** ||
|---|---|
| **Type** | **Description** |
| `int|string` |   |

### setTrueNegativeCount

Output only. The number of labels that were not created by the model,
but if they would, they would not match a ground truth label.

| **Parameter** ||
|---|---|
| **Name** | **Description** |
| `var` | `int|string` |

| **Returns** ||
|---|---|
| **Type** | **Description** |
| `$this` |   |