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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: 7988119488817b15785e720ba66a9369
size: 2771
params:
params.yaml:
load_dataset.bucket: datasetbucket
load_dataset.filename: WineQT.csv
load_dataset.raw_data: /data/raw
outs:
- path: ./data/raw/WineQT.csv
hash: md5
md5: c4ca69c2088b0d7fe9be7e8d33106695
size: 71823
make_dataset:
cmd: python ./src/data/make_dataset.py
deps:
- path: ./data/raw/WineQT.csv
hash: md5
md5: c4ca69c2088b0d7fe9be7e8d33106695
size: 71823
- path: ./src/data/make_dataset.py
hash: md5
md5: a9481f3d760e375c06e6d635650aa12b
size: 3308
params:
params.yaml:
load_dataset.filename: WineQT.csv
load_dataset.raw_data: /data/raw
make_dataset.processed_data: /data/interim
make_dataset.res_seed: 42
make_dataset.seed: 41
make_dataset.test_split: 0.25
outs:
- path: ./data/interim/test.csv
hash: md5
md5: d602beee05ac17a0ab3d7a0d9d3dfb5e
size: 104399
- path: ./data/interim/train.csv
hash: md5
md5: 08e6766c37a3c7e95be58327f2cfe604
size: 313662
build_features:
cmd: python ./src/features/build_features.py
deps:
- path: ./data/interim/test.csv
hash: md5
md5: d602beee05ac17a0ab3d7a0d9d3dfb5e
size: 104399
- path: ./data/interim/train.csv
hash: md5
md5: 08e6766c37a3c7e95be58327f2cfe604
size: 313662
- path: ./src/features/build_features.py
hash: md5
md5: 5c9a4bfa2cb6aca2ec318493200f0f04
size: 4408
params:
params.yaml:
build_features.processed_data: /data/processed
make_dataset.processed_data: /data/interim
outs:
- path: ./data/processed/processed_test.csv
hash: md5
md5: 800eaaba8517a91df2d1d58fe7fb19d6
size: 91615
- path: ./data/processed/processed_train.csv
hash: md5
md5: e12ca6b9bf2885df081b6bfafab64aa9
size: 273896
train_model:
cmd: python ./src/models/train_model.py
deps:
- path: ./data/processed/processed_test.csv
hash: md5
md5: 800eaaba8517a91df2d1d58fe7fb19d6
size: 91615
- path: ./data/processed/processed_train.csv
hash: md5
md5: e12ca6b9bf2885df081b6bfafab64aa9
size: 273896
- path: ./src/models/train_model.py
hash: md5
md5: b9f38cf0319063fedfd0e7beb622f413
size: 5661
params:
params.yaml:
base.target: quality
build_features.processed_data: /data/processed
mlflow_config.remote_server_uri: http://localhost:5000
mlflow_config.trainingExpName: Trained Models
train_model.criterion: gini
train_model.max_depth: 18
train_model.min_samples_leaf: 30
train_model.min_samples_split: 60
train_model.model_dir: /models
train_model.n_estimators: 100
train_model.random_state: 42
outs:
- path: ./models/model.joblib
hash: md5
md5: a3301e8a6b4e4daf59f35b986866ef1f
size: 826633
tune_model:
cmd: python ./src/models/tune_model.py
deps:
- path: ./data/processed/processed_test.csv
hash: md5
md5: 800eaaba8517a91df2d1d58fe7fb19d6
size: 91615
- path: ./data/processed/processed_train.csv
hash: md5
md5: e12ca6b9bf2885df081b6bfafab64aa9
size: 273896
- path: ./src/models/tune_model.py
hash: md5
md5: d1ff6f5922a0dac1c499d8d7116fe351
size: 7968
params:
params.yaml:
base.target: quality
build_features.processed_data: /data/processed
hyperopt.max_eval: 10
hyperopt.model_name: best_model
mlflow_config.remote_server_uri: http://localhost:5000
mlflow_config.tunningExpName: Tunned Models
outs:
- path: ./models/best_model.joblib
hash: md5
md5: f9e89f459eed1402c7b0fc6e39450c9a
size: 2525273