TopicNet Recipes

This module contains mechanisms to generate code for training topic models on your data. It was created in orded to simplify knowledge transition about model training from the field researchers to the end users and possibly for easier exchange of a code between the research groups. As a backbone it uses snippets of YAML configs that require filling in information about the collection and hyperparameters of the required topic model. Currently it is recommended to import BaselineRecipe, SearchRecipe, MultimodalSearchRecipe classes for the experiment environment generation. However, for the compatibility with previous examples found in topicnet/demos/*-Recipe.ipynb notebooks we also have ARTM-baseline and exploratory_search configs in YAML format.

• BaselineRecipe - Class for generating a pipeline training a topic models with decorrelation regularization, maximizing custom BleiLafferty score from TopicNet library topicnet.cooking_machine.models.scores.BleiLaffertyScore.
• SearchRecipe - a Class recreating training scenario from exploratory_search YAML config. Provides good startegy for training topic models for collection search properties. A link to the publication can be found in the comments section of the recipe.
• MultimodalSearchRecipe - a Class that modifies previos strategy for the case of multimodal data allowing to recreate previous scenario for each modality separately.
• intratext_coherence_maximization.yml - a strin in YAML format (like the old recipes) allowing to build topic model with decorrelation, Phi and Theta matrices Sparsing and Smoothing with background topics maximizing the intratext coherence score topicnet.cooking_machine.models.scores.IntratextCoherenceScore.
• topic_number_search.yml - a recipe recreating published strategy to find optimal topic number for given dataset. References to the publication can be found in the config dosctring.

from .multimodal_exploratory_search_pipeline import MultimodalSearchRecipe
from .artm_baseline_pipeline import BaselineRecipe
from .intratext_coherence_pipeline import IntratextCoherenceRecipe
from .exploratory_search_pipeline import SearchRecipe
from .artm_baseline_pipeline import ARTM_baseline_template as ARTM_baseline
from .exploratory_search_pipeline import exploratory_search_template as exploratory_search