import * as tf from '@tensorflow/tfjs';
import * as types from '../../../types';
import { EmbeddingsModel } from '../embeddings/EmbeddingsModel';
export default class ClassificationModel extends types.PipelineModel implements types.IPipelineModel {
    private static setup;
    private config;
    private datasetParams;
    private model;
    private embeddingsModel;
    private logger;
    private classificationTrainStatsHandler;
    constructor(config: types.IClassificationModelParams & types.IDefaultModelParams, datasetParams: types.IDatasetParams, embeddingsModel: EmbeddingsModel, logger: types.IPipelineModelLogger, pretrainedModel?: tf.LayersModel, classificationTrainStatsHandler?: types.ITrainStatsHandler['classification']);
    tfModel: () => tf.LayersModel;
    predict: (sentences: string[]) => types.IClassificationPred[];
    train: (trainDataset: types.ITrainingParams) => Promise<void>;
    test: (testExamples: types.ITestingParams, resultsHandler?: types.ITestPredictionsHandler | undefined) => Promise<types.IPredictionStats>;
    private defaultResultsLogger;
}