The present invention relates to information retrieval. In order to facilitate a search and identification of documents, there is provided a computer-implemented method for training a classifier model for data classification in response to a search query. The computer-implemented method comprises:



a) obtaining a dataset that comprises a seed set of labeled data representing a training dataset;
b) training the classifier model by using the training dataset to fit parameters of the classifier model;
c) evaluating a quality of the classifier model using a test dataset that comprises unlabeled data from the obtained dataset to generate a classifier confidence score indicative of a probability of correctness of the classifier model working on the test dataset;
d) determining a global risk value of misclassification and a reward value based on the classifier confidence score on the test dataset;
e) iteratively updating the parameters of the classifier model and performing steps b) to d) until the global risk value falls within a predetermined risk limit value or an expected reward value is reached.