Files related to pylearn-users topic: https://groups.google.com/forum/#!topic/pylearn-users/a1sjKKIC2BY

csv_dataset_test.csv

csv_dataset_test.yaml

!obj:pylearn2.train.Train {
    dataset: &train !obj:pylearn2.datasets.csv_dataset.CSVDataset {
        path: 'csv_dataset_test.csv',
        task: 'regression'
    },
    model: !obj:pylearn2.models.mlp.MLP {
        layers: [
                 !obj:pylearn2.models.mlp.RectifiedLinear {
                     layer_name: 'h0',
                     dim: 150,
                     sparse_init: 1,
                     use_bias: True
                 },
                 !obj:pylearn2.models.mlp.Linear {
                     layer_name: 'y',
                     sparse_init: 1,
                     dim: 1,
                 }
                ],
        nvis: 21,
    },
    algorithm: !obj:pylearn2.training_algorithms.sgd.SGD {
        batch_size: 10,
        learning_rate: .002,
        learning_rule: !obj:pylearn2.training_algorithms.learning_rule.Momentum {
            init_momentum: .05
        },
        monitoring_dataset:
            {
                'train' : *train,
                'valid' : !obj:pylearn2.datasets.csv_dataset.CSVDataset {
                    path: 'csv_dataset_valid.csv',
                    task: 'regression'
                },
            },
        termination_criterion: !obj:pylearn2.termination_criteria.EpochCounter {
            max_epochs: 150
        }
    },
    extensions: [
        !obj:pylearn2.train_extensions.best_params.MonitorBasedSaveBest {
            channel_name: "valid_objective",
            save_path: "best_Jonas.pkl"
        }
    ]
}

csv_dataset_valid.csv