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dvc.lock
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schema: '2.0'
stages:
load_dataset:
cmd: python ./src/data/load_dataset.py
deps:
- path: ./src/data/load_dataset.py
hash: md5
md5: 66e46ce7e93b2c343cb1fff2b8ec22de
size: 2120
params:
params.yaml:
load_dataset.drive_link:
https://drive.google.com/file/d/1FCVWcNyBX6tFYjfORhnAvIwS8I8zV92j/view?usp=sharing
load_dataset.file_name: wineq
load_dataset.raw_data: /data/raw
outs:
- path: ./data/raw/wineq.csv
hash: md5
md5: 3155f71c567752e38f24f887ce0c4ef8
size: 72970
make_dataset:
cmd: python ./src/data/make_dataset.py
deps:
- path: ./data/raw/wineq.csv
hash: md5
md5: 3155f71c567752e38f24f887ce0c4ef8
size: 72970
- path: ./src/data/make_dataset.py
hash: md5
md5: 8bf252df39adfc976db6502ac8a7bd28
size: 3698
params:
params.yaml:
load_dataset.file_name: wineq
load_dataset.raw_data: /data/raw
make_dataset.processed_data: /data/processed
make_dataset.res_seed: 42
make_dataset.seed: 41
make_dataset.test_split: 0.25
outs:
- path: ./data/processed/test.csv
hash: md5
md5: ad48d3c4e5f3a042ccf540a6e237bd5c
size: 104695
- path: ./data/processed/train.csv
hash: md5
md5: 65f8c437f89c9ab2b9a724feb0056432
size: 314608
build_features:
cmd: python ./src/features/build_features.py
deps:
- path: ./data/processed/test.csv
hash: md5
md5: ad48d3c4e5f3a042ccf540a6e237bd5c
size: 104695
- path: ./data/processed/train.csv
hash: md5
md5: 65f8c437f89c9ab2b9a724feb0056432
size: 314608
- path: ./src/features/build_features.py
hash: md5
md5: ac74288d13827cfe74b370cb76d4a8df
size: 3229
params:
params.yaml:
build_features.extended_data: /data/extended
make_dataset.processed_data: /data/processed
outs:
- path: ./data/extended/extended_test.csv
hash: md5
md5: 56ef2daa1f6940621c3ba0f87e10b0c1
size: 200566
- path: ./data/extended/extended_train.csv
hash: md5
md5: db4ce59faea54e04dae93af1e942f4c2
size: 601982
train_model:
cmd: python ./src/models/train_model.py
deps:
- path: ./data/extended/extended_test.csv
hash: md5
md5: 56ef2daa1f6940621c3ba0f87e10b0c1
size: 200566
- path: ./data/extended/extended_train.csv
hash: md5
md5: db4ce59faea54e04dae93af1e942f4c2
size: 601982
- path: ./src/models/train_model.py
hash: md5
md5: a74f763ded5dd5b54217be40162cea3f
size: 5884
params:
params.yaml:
base.target: quality
build_features.extended_data: /data/extended
mlflow_config.remote_server_uri: http://localhost:5000
mlflow_config.trainingExpName: modeltraining
train_model.criterion: gini
train_model.max_depth: 50
train_model.min_samples_leaf: 30
train_model.min_samples_split: 60
train_model.model_dir: /models
train_model.n_estimators: 50
train_model.random_state: 42
outs:
- path: ./models/model.joblib
hash: md5
md5: 2abc3afc802ff579283b38e32e5a3190
size: 141177
tune_model:
cmd: python ./src/models/tune_model.py
deps:
- path: ./data/extended/extended_test.csv
hash: md5
md5: 56ef2daa1f6940621c3ba0f87e10b0c1
size: 200566
- path: ./data/extended/extended_train.csv
hash: md5
md5: db4ce59faea54e04dae93af1e942f4c2
size: 601982
- path: ./src/models/tune_model.py
hash: md5
md5: b82ee90750a841620d81bb9e97e02796
size: 8258
params:
params.yaml:
base.target: quality
build_features.extended_data: /data/extended
hyperopt.max_eval: 1
hyperopt.model_name: best_model
mlflow_config.remote_server_uri: http://localhost:5000
mlflow_config.tunningExpName: modeltunning
outs:
- path: ./models/best_model.joblib
hash: md5
md5: da0e91c46198ff9229b07fb8e3302c34
size: 164697