default.portfolio
config_predictor_tuple
def config_predictor_tuple(tasks, configs, meta_features, regret_matrix)
Config predictor represented in tuple.
The returned tuple consists of (meta_features, preferences, proc).
Returns:
meta_features_norm
- A dataframe of normalized meta features, each column for a task.preferences
- A dataframe of sorted configuration indicies by their performance per task (column).regret_matrix
- A dataframe of the configuration(row)-task(column) regret matrix.
build_portfolio
def build_portfolio(meta_features, regret, strategy)
Build a portfolio from meta features and regret matrix.
Arguments:
meta_features
- A dataframe of metafeatures matrix.regret
- A dataframe of regret matrix.strategy
- A str of the strategy, one of ("greedy", "greedy-feedback").
load_json
def load_json(filename)
Returns the contents of json file filename.
serialize
def serialize(configs, regret, meta_features, output_file, config_path)
Store to disk all information FLAML-metalearn needs at runtime.
configs: names of model configs regret: regret matrix meta_features: task metafeatures output_file: filename config_path: path containing config json files