149 lines
4.0 KiB
YAML
149 lines
4.0 KiB
YAML
baseline_experiments:
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- name: "bigru"
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description: "Baseline BiGRU with full name features"
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model_type: "bigru"
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features: [ "full_name" ]
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model_params:
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max_len: 20
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embedding_dim: 64
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gru_units: 32
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epochs: 2
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batch_size: 32
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tags: [ "baseline", "neural", "bigru" ]
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- name: "cnn"
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description: "Baseline CNN with character patterns"
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model_type: "cnn"
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features: [ "full_name" ]
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model_params:
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max_len: 20
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embedding_dim: 64
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filters: 64
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kernel_size: 3
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dropout: 0.5
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epochs: 2
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batch_size: 32
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tags: [ "baseline", "neural", "cnn" ]
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- name: "ensemble"
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description: "Baseline Ensemble with multiple models"
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model_type: "ensemble"
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features: [ "full_name", "name_length", "word_count" ]
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model_params:
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base_models: [ "logistic_regression", "random_forest", "xgboost" ]
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voting: "soft"
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cv_folds: 5
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tags: [ "baseline", "ensemble" ]
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- name: "lightgbm"
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description: "Baseline LightGBM with engineered features"
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model_type: "lightgbm"
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features: [ "full_name", "name_length", "word_count" ]
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model_params:
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n_estimators: 100
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max_depth: -1
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learning_rate: 0.1
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num_leaves: 31
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subsample: 0.8
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colsample_bytree: 0.8
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tags: [ "baseline", "lightgbm" ]
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- name: "logistic_regression_fullname"
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description: "Baseline logistic regression with full name"
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model_type: "logistic_regression"
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features: [ "full_name" ]
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model_params:
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max_features: 10000
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tags: [ "baseline", "logistic_regression", "fullname" ]
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- name: "logistic_regression_native"
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description: "Logistic regression with native name only"
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model_type: "logistic_regression"
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features: [ "native_name" ]
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model_params:
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max_features: 5000
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tags: [ "baseline", "logistic_regression", "native" ]
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- name: "logistic_regression_surname"
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description: "Logistic regression with surname name only"
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model_type: "logistic_regression"
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features: [ "surname" ]
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model_params:
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max_features: 5000
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tags: [ "baseline", "logistic_regression", "surname" ]
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- name: "lstm"
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description: "Baseline LSTM with full name features"
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model_type: "lstm"
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features: [ "full_name" ]
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model_params:
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embedding_dim: 128
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lstm_units: 64
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epochs: 2
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batch_size: 64
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tags: [ "baseline", "neural", "lstm" ]
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- name: "naive_bayes"
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description: "Baseline Naive Bayes with full name features"
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model_type: "naive_bayes"
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features: [ "full_name" ]
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model_params:
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max_features: 5000
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tags: [ "baseline", "naive_bayes" ]
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- name: "random_forest"
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description: "Baseline Random Forest with engineered features"
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model_type: "random_forest"
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features: [ "name_length", "word_count", "province" ]
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model_params:
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n_estimators: 100
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max_depth: 10
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min_samples_split: 2
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min_samples_leaf: 1
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tags: [ "baseline", "random_forest", "engineered" ]
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- name: "svm"
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description: "Baseline SVM with full name features"
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model_type: "svm"
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features: [ "full_name" ]
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model_params:
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C: 1.0
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kernel: "rbf"
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ngram_range: [ 2, 4 ]
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max_features: 5000
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tags: [ "baseline", "svm" ]
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- name: "transformer"
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description: "Baseline Transformer with attention mechanism"
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model_type: "transformer"
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features: [ "full_name" ]
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model_params:
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embedding_dim: 128
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num_heads: 4
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num_layers: 2
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epochs: 2
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batch_size: 64
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tags: [ "baseline", "neural", "transformer" ]
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- name: "xgboost"
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description: "Baseline XGBoost with engineered features"
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model_type: "xgboost"
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features: [ "full_name", "name_length", "word_count" ]
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model_params:
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n_estimators: 100
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max_depth: 6
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learning_rate: 0.1
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subsample: 0.8
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colsample_bytree: 0.8
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tags: [ "baseline", "xgboost" ]
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# Advanced Experiments Configuration
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advanced_experiments:
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# Feature Study Configurations
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feature_studies:
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# Hyperparameter Tuning Configurations
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hyperparameter_tuning:
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