Description: Through the scikit-learn library, the tf.contrib.learn function is used to generate three layers of neural network model, and the data is trained directly, and the data can be predicted.
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boston
boston\boston.py
boston\models
boston\models\dnnregressor
boston\models\dnnregressor\checkpoint
boston\models\dnnregressor\eval
boston\models\dnnregressor\eval\events.out.tfevents.1505876573.ADMIN-PC
boston\models\dnnregressor\eval\events.out.tfevents.1505876614.ADMIN-PC
boston\models\dnnregressor\events.out.tfevents.1505876555.ADMIN-PC
boston\models\dnnregressor\events.out.tfevents.1505876596.ADMIN-PC
boston\models\dnnregressor\graph.pbtxt
boston\models\dnnregressor\model.ckpt-1.data-00000-of-00001
boston\models\dnnregressor\model.ckpt-1.index
boston\models\dnnregressor\model.ckpt-1.meta
boston\models\dnnregressor\model.ckpt-10000.data-00000-of-00001
boston\models\dnnregressor\model.ckpt-10000.index
boston\models\dnnregressor\model.ckpt-10000.meta
boston\models\dnnregressor\model.ckpt-5000.data-00000-of-00001
boston\models\dnnregressor\model.ckpt-5000.index
boston\models\dnnregressor\model.ckpt-5000.meta
boston\models\dnnregressor\model.ckpt-5001.data-00000-of-00001
boston\models\dnnregressor\model.ckpt-5001.index
boston\models\dnnregressor\model.ckpt-5001.meta
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