[**@s4ai/core Documentation v0.3.23**](../../../README.md)

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[@s4ai/core Documentation](../../../modules.md) / [@s4ai/core](../README.md) / MLMLearningOptimizer

# Class: MLMLearningOptimizer

Defined in: intelligence/mlm-learning-optimizer.js:9

## Constructors

### Constructor

> **new MLMLearningOptimizer**(): `MLMLearningOptimizer`

Defined in: intelligence/mlm-learning-optimizer.js:10

#### Returns

`MLMLearningOptimizer`

## Properties

### confidenceThreshold

> **confidenceThreshold**: `number`

Defined in: intelligence/mlm-learning-optimizer.js:12

***

### metrics

> **metrics**: `object`

Defined in: intelligence/mlm-learning-optimizer.js:13

#### accuracy\_rate

> **accuracy\_rate**: `number` = `0`

#### false\_positives

> **false\_positives**: `number` = `0`

#### high\_confidence\_patterns

> **high\_confidence\_patterns**: `number` = `0`

#### total\_patterns

> **total\_patterns**: `number` = `0`

#### validated\_patterns

> **validated\_patterns**: `number` = `0`

***

### targetAccuracy

> **targetAccuracy**: `number`

Defined in: intelligence/mlm-learning-optimizer.js:11

## Methods

### analyzeLearningAccuracy()

> **analyzeLearningAccuracy**(): `Promise`\<\{ `accuracy_by_domain`: \{ \}; `high_confidence_patterns`: `any`; `overall_metrics`: \{ `accuracy_rate`: `number`; `false_positives`: `number`; `high_confidence_patterns`: `number`; `total_patterns`: `number`; `validated_patterns`: `number`; \}; \} \| `null`\>

Defined in: intelligence/mlm-learning-optimizer.js:25

Analyze learning patterns and calculate accuracy

#### Returns

`Promise`\<\{ `accuracy_by_domain`: \{ \}; `high_confidence_patterns`: `any`; `overall_metrics`: \{ `accuracy_rate`: `number`; `false_positives`: `number`; `high_confidence_patterns`: `number`; `total_patterns`: `number`; `validated_patterns`: `number`; \}; \} \| `null`\>

***

### analyzeLearningVelocity()

> **analyzeLearningVelocity**(): `Promise`\<\{ `learning_rate`: \{ `avg_confidence`: `string`; `daily_breakdown`: `any`; `patterns_per_day`: `string`; \}; `recommendations`: \{ `learning_adjustment`: `string`; `trend`: `string`; `update_frequency`: `string`; \}; \} \| `null`\>

Defined in: intelligence/mlm-learning-optimizer.js:173

Analyze learning velocity and optimal update frequency

#### Returns

`Promise`\<\{ `learning_rate`: \{ `avg_confidence`: `string`; `daily_breakdown`: `any`; `patterns_per_day`: `string`; \}; `recommendations`: \{ `learning_adjustment`: `string`; `trend`: `string`; `update_frequency`: `string`; \}; \} \| `null`\>

***

### getConfidenceOptimizations()

> **getConfidenceOptimizations**(): `object`

Defined in: intelligence/mlm-learning-optimizer.js:139

Optimize confidence scoring algorithm

#### Returns

`object`

##### current\_algorithm

> **current\_algorithm**: `string` = `'confidence = base_score * (1 + boost_factors)'`

##### estimated\_improvement

> **estimated\_improvement**: `string` = `'+45% overall accuracy'`

##### factors

> **factors**: `object`

###### factors.domain\_consistency

> **domain\_consistency**: `object`

###### factors.domain\_consistency.description

> **description**: `string` = `'Patterns consistent across related domains are more trustworthy'`

###### factors.domain\_consistency.formula

> **formula**: `string` = `'consistency_factor = 1.0 + (related_domain_matches / max_related)'`

###### factors.domain\_consistency.impact

> **impact**: `string` = `'+8% accuracy'`

###### factors.frequency\_factor

> **frequency\_factor**: `object`

###### factors.frequency\_factor.description

> **description**: `string` = `'Patterns that occur frequently are more likely accurate'`

###### factors.frequency\_factor.formula

> **formula**: `string` = `'frequency_factor = 1.0 + log10(occurrences) / 3'`

###### factors.frequency\_factor.impact

> **impact**: `string` = `'+10% accuracy'`

###### factors.recency\_factor

> **recency\_factor**: `object`

###### factors.recency\_factor.description

> **description**: `string` = `'Recent patterns are more relevant'`

###### factors.recency\_factor.formula

> **formula**: `string` = `'recency_factor = 1.0 + (1 - (days_since_pattern / 30))'`

###### factors.recency\_factor.impact

> **impact**: `string` = `'+12% accuracy'`

###### factors.validation\_factor

> **validation\_factor**: `object`

###### factors.validation\_factor.description

> **description**: `string` = `'Increase confidence if pattern led to successful Q-DD decision'`

###### factors.validation\_factor.formula

> **formula**: `string` = `'validation_factor = qdd_success_rate if exists else 1.0'`

###### factors.validation\_factor.impact

> **impact**: `string` = `'+15% accuracy'`

##### implementation\_effort

> **implementation\_effort**: `string` = `'MEDIUM (2-3 days)'`

##### recommended\_algorithm

> **recommended\_algorithm**: `string` = `'confidence = base_score * (1 + validation_factor) * (1 + recency_factor) * (1 + frequency_factor)'`

***

### getOptimizationRecommendations()

> **getOptimizationRecommendations**(): `Promise`\<\{ `optimization_roadmap`: `object`[]; `overall_assessment`: \{ `accuracy`: `string`; `action`: `string`; `message`: `string`; `status`: `string`; \}; `recommendations`: (\{ `action`: `string`; `count?`: `undefined`; `current?`: `undefined`; `current_rate`: `string`; `estimated_improvement`: `string`; `issue`: `string`; `priority`: `string`; `target?`: `undefined`; `target_rate`: `string`; \} \| \{ `action`: `string`; `count`: `any`; `current?`: `undefined`; `current_rate?`: `undefined`; `estimated_improvement`: `string`; `issue`: `string`; `priority`: `string`; `target?`: `undefined`; `target_rate?`: `undefined`; \} \| \{ `action`: `string`; `count?`: `undefined`; `current`: `string`; `current_rate?`: `undefined`; `estimated_improvement`: `string`; `issue`: `string`; `priority`: `string`; `target`: `string`; `target_rate?`: `undefined`; \})[]; \}\>

Defined in: intelligence/mlm-learning-optimizer.js:215

Generate learning optimization recommendations

#### Returns

`Promise`\<\{ `optimization_roadmap`: `object`[]; `overall_assessment`: \{ `accuracy`: `string`; `action`: `string`; `message`: `string`; `status`: `string`; \}; `recommendations`: (\{ `action`: `string`; `count?`: `undefined`; `current?`: `undefined`; `current_rate`: `string`; `estimated_improvement`: `string`; `issue`: `string`; `priority`: `string`; `target?`: `undefined`; `target_rate`: `string`; \} \| \{ `action`: `string`; `count`: `any`; `current?`: `undefined`; `current_rate?`: `undefined`; `estimated_improvement`: `string`; `issue`: `string`; `priority`: `string`; `target?`: `undefined`; `target_rate?`: `undefined`; \} \| \{ `action`: `string`; `count?`: `undefined`; `current`: `string`; `current_rate?`: `undefined`; `estimated_improvement`: `string`; `issue`: `string`; `priority`: `string`; `target`: `string`; `target_rate?`: `undefined`; \})[]; \}\>

***

### getOverallAssessment()

> **getOverallAssessment**(): `object`

Defined in: intelligence/mlm-learning-optimizer.js:290

Get overall learning system assessment

#### Returns

`object`

##### accuracy

> **accuracy**: `string`

##### action

> **action**: `string` = `'Monitor for degradation, continue validation'`

##### message

> **message**: `string` = `'System is learning accurately at 90%+ confidence level'`

##### status

> **status**: `string` = `'✓ OPTIMAL'`

***

### identifyFalsePositives()

> **identifyFalsePositives**(): `Promise`\<\{ `false_positive_patterns`: `any`; `recommendation`: `string`; `total_false_positives`: `any`; \} \| `null`\>

Defined in: intelligence/mlm-learning-optimizer.js:99

Identify and analyze false positives

#### Returns

`Promise`\<\{ `false_positive_patterns`: `any`; `recommendation`: `string`; `total_false_positives`: `any`; \} \| `null`\>