ML_Intern/params.yaml

impute:
  class: SimpleImputer
  module: sklearn.impute
  params:
    strategy: "median"

train_test_split:
  class: train_test_split
  module: sklearn.model_selection
  params:
    test_size: 0.2
    random_state: 43

grid_search:
  class: GridSearchCV
  module: sklearn.model_selection
  params:
    cv: [5,6,7,8,9,10]
    verbose: 2
  
model_selection:
  module_0:
    class: LinearRegression
    module: sklearn.linear_model
    params:
      fit_intercept: True
    search_param_grid:
      fit_intercept:
      - true
      - false
  module_1:
    class: RandomForestRegressor
    module: sklearn.ensemble
    params:
      min_sample_leaf: 3
    search_param_grid:
      min_sample_leaf:
      - 6

randomized_search:
  class: RandomizedSearchCV
  module: sklearn.model_selection
  params:
    n_estimators: [100,200,300,400,500,600,700,750,800,850,900,950,1000]
    max_features: ["auto", "sqrt"]
    max_depth: [4,5,10,15,20,25,30,35,40,50,60,75,100,110,120,150]
    min_samples_split: [2,5,10,15,20,50,100]
    min_samples_leaf: [2,5,4,9,6,30,33,50,75,100]
  scoring: 'neg_mean_squared_error'
  n_iter: 10
  cv: 5
  verbose: 2
  random_state: 43