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Machine Learning for Healthcare Analytics Projects

You're reading from   Machine Learning for Healthcare Analytics Projects Build smart AI applications using neural network methodologies across the healthcare vertical market

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Product type Paperback
Published in Oct 2018
Publisher Packt
ISBN-13 9781789536591
Length 134 pages
Edition 1st Edition
Languages
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Author (1):
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Eduonix Learning Solutions Eduonix Learning Solutions
Author Profile Icon Eduonix Learning Solutions
Eduonix Learning Solutions
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Toc

Building our Keras model

We'll now start building our Keras model, which is a deep learning algorithm:

  1. The first thing that we're going to do is import the necessary packages and layers. We will do that by running the following lines of code:
from sklearn.model_selection import GridSearchCV, KFold
from keras.models import Sequential
from keras.layers import Dense
from keras.wrappers.scikit_learn import KerasClassifier
from keras.optimizers import Adam

In the preceding code snippet , GridSearchCV is the function we will use to perform a grid search, and KFold will be used for performing the k-fold cross-validation. KerasClassifier is used as the wrapper. Adam is the optimizer that we will be using for this model; the rest of the functions are all general functions used to define the model:

  1. Let's start by defining the model. We will use a create_model() function, because...
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