MODEL LEARNING APPARATUS, DATA ANALYSIS APPARATUS, MODEL LEARNING METHOD AND PROGRAM

1 . A model learning apparatus, comprising:

a memory; and

one or more processors configured to:

train an unsupervised deep learning model using training data;

calculate a correlation between input dimensions in the deep learning model; and

train an analysis model using the training data for each set of dimensions having a correlation.

2 . The model learning apparatus according to claim 1 , wherein the model learning apparatus is configured to calculate a contribution degree for a final output value of each of dimensions of input data in the deep learning model, and calculate a correlation between input dimensions based on the contribution degree.

3 . The model learning apparatus of claim 1 , wherein the one or more processors are configured to perform data analysis using an analysis model trained by the division model learning unit.

4 . The model learning apparatus of claim 1 , wherein the one or more processors are configured to:

divide dimensions of training data into a plurality of groups and train an unsupervised deep learning model using divided training data for each of the groups;

calculate a correlation between input dimensions in the deep learning model for each of the groups;

train division models using the training data for each set of dimensions having a correlation, for each of the groups;

train a deep learning model using a feature obtained from each of the division models for each of the groups; and

train the analysis model using the training data for each set of dimensions having a correlation between input dimensions in the deep learning model.

5 . The model learning apparatus of claim 4 , wherein the one or more processors configured to perform data analysis using an analysis model trained by the learning unit described in claim 4 .

6 . A model learning method performed by a model learning apparatus comprising one or more processors, the model learning method comprising:

training, by the one or more processors, an unsupervised deep learning model using training data;

calculating, by the one or more processors, a correlation between input dimensions in the deep learning model; and

training, by the one or more processors, an analysis model using the training data for each set of dimensions having a correlation.

7 . The model learning method of claim 1 , further comprising:

dividing dimensions of training data into a plurality of groups;

training an unsupervised deep learning model using divided training data for each of the groups;

calculating a correlation between input dimensions in the deep learning model for each of the groups;

training division models using the training data for each set of dimensions having a correlation, for each of the groups;

training a deep learning model using a feature obtained from each of the division models for each of the groups; and

training the analysis model using the training data for each set of dimensions having a correlation between input dimensions in the deep learning model.

8 . A non-transitory recording medium storing instructions of a program for causing a computer to perform operations comprising:

training an unsupervised deep learning model using training data;

calculating a correlation between input dimensions in the deep learning model; and

training an analysis model using the training data for each set of dimensions having a correlation.