predict

Generates predictions for user behavior and action recommendations.

Uses the trained neural network to analyze context data and produce confidence scores for next actions, timing predictions, and preference alignment.

Prediction Process:

1. Feature extraction from most recent interaction

2. Forward propagation through neural network

3. Confidence score generation and tracking

4. Result packaging with metadata

Output Interpretation:

• next_action_confidence: Likelihood of suggested action success 0, 1

• timing_prediction: Temporal urgency or scheduling priority 0, 1

• preference_score: User preference alignment score 0, 1

Thread Safety: Uses mutex for concurrent prediction requests Performance: O(1) inference time with fixed network size

Parameters

See also