katana-assistant
# Compile model. Stochastic gradient descent with Nesterov accelerated gradient gives good results for this modelsgd = SGD(lr=0.01, decay=1e-6, momentum=0.9, nesterov=True)model.compile(loss='categorical_crossentropy', optimizer=sgd, metrics=['accuracy'])katana-assistant
classify_local('Fetch blood result for patient')katana-assistant
45 documents9 classes ['adverse_drug', 'blood_pressure', 'blood_pressure_search', 'goodbye', 'greeting', 'hospital_search', 'options', 'pharmacy_search', 'thanks']82 unique stemmed words ["'s", ',', 'a', 'advers', 'al', 'anyon', 'ar', 'awesom', 'be', 'behavy', 'blood', 'by', 'bye', 'can', 'caus', 'chat', 'check', 'could', 'dat', 'day', 'detail', 'do', 'dont', 'drug', 'entry', 'find', 'for', 'giv', 'good', 'goodby', 'hav', 'hello', 'help', 'hi', 'hist', 'hospit', 'how', 'i', 'id', 'is', 'lat', 'list', 'load', 'loc', 'log', 'look', 'lookup', 'man', 'me', 'mod', 'nearby', 'next', 'nic', 'of', 'off', 'op', 'paty', 'pharm', 'press', 'provid', 'react', 'rel', 'result', 'search', 'see', 'show', 'suit', 'support', 'task', 'thank', 'that', 'ther', 'til', 'tim', 'to', 'transf', 'up', 'want', 'what', 'which', 'with', 'you']katana-assistant
# Fit the modelmodel.fit(np.array(train_x), np.array(train_y), epochs=200, batch_size=5, verbose=1)katana-assistant
# Create model - 3 layers. First layer 128 neurons, second layer 64 neurons and 3rd output layer contains number of neurons# equal to number of intents to predict output intent with softmaxmodel = Sequential()model.add(Dense(128, input_shape=(len(train_x[0]),), activation='relu'))model.add(Dropout(0.5))model.add(Dense(64, activation='relu'))model.add(Dropout(0.5))model.add(Dense(len(train_y[0]), activation='softmax'))katana-assistant
p = bow("Load blood pessure for patient", words)print (p)print (classes)katana-assistant
import nltkfrom nltk.stem.lancaster import LancasterStemmerstemmer = LancasterStemmer()# things we need for Tensorflowimport numpy as npfrom keras.models import Sequentialfrom keras.layers import Dense, Activation, Dropoutfrom keras.optimizers import SGDimport pandas as pdimport pickleimport randomCopyright © 2021 Codeinu
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