From 1dbbeba6630d88afa7444c90d1239ade63399ac5 Mon Sep 17 00:00:00 2001
From: abhishek <36329206+Mario263@users.noreply.github.com>
Date: Mon, 1 Nov 2021 10:35:39 +0530
Subject: [PATCH] Added Model to predict cancer tumour size

---
 Cancer Tumour size prediction model/model.py | 2029 ++++++++++++++++++
 1 file changed, 2029 insertions(+)
 create mode 100644 Cancer Tumour size prediction model/model.py

diff --git a/Cancer Tumour size prediction model/model.py b/Cancer Tumour size prediction model/model.py
new file mode 100644
index 0000000..a333107
--- /dev/null
+++ b/Cancer Tumour size prediction model/model.py	
@@ -0,0 +1,2029 @@
+import pandas as pd
+import numpy as np
+dataset = pd.read_csv('/content/cancer.csv')
+x = dataset.drop(columns=['diagnosis(1=m, 0=b)'])
+y = dataset['diagnosis(1=m, 0=b)']
+from sklearn.model_selection import train_test_split
+​
+x_train, x_test, y_train, y_test = train_test_split(x,y,test_size=0.2)
+import tensorflow as tf
+model = tf.keras.models.Sequential()
+model.add(tf.keras.layers.Dense(256, input_shape=x_train.shape, activation='sigmoid'))
+model.add(tf.keras.layers.Dense(256, activation='sigmoid'))
+model.add(tf.keras.layers.Dense(1, activation='sigmoid'))
+model.add(tf.keras.layers.Dense(256, input_shape=x_train.shape, activation='sigmoid'))
+model.add(tf.keras.layers.Dense(256, activation='sigmoid'))
+model.add(tf.keras.layers.Dense(1, activation='sigmoid'))
+model.compile(optimizer='adam', loss='binary_crossentropy', metrics=['accuracy'])
+
+model.fit(x_train, y_train, epochs=1000)
+
+Epoch 1/1000
+WARNING:tensorflow:Model was constructed with shape (None, 455, 30) for input KerasTensor(type_spec=TensorSpec(shape=(None, 455, 30), dtype=tf.float32, name='dense_input'), name='dense_input', description="created by layer 'dense_input'"), but it was called on an input with incompatible shape (None, 30).
+WARNING:tensorflow:Model was constructed with shape (None, 455, 30) for input KerasTensor(type_spec=TensorSpec(shape=(None, 455, 30), dtype=tf.float32, name='dense_input'), name='dense_input', description="created by layer 'dense_input'"), but it was called on an input with incompatible shape (None, 30).
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+Epoch 2/1000
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+Epoch 3/1000
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+Epoch 4/1000
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+Epoch 5/1000
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+Epoch 6/1000
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+Epoch 7/1000
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+Epoch 8/1000
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+Epoch 9/1000
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+Epoch 10/1000
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+Epoch 11/1000
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+Epoch 12/1000
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+Epoch 13/1000
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+Epoch 14/1000
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+Epoch 15/1000
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+Epoch 16/1000
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+Epoch 17/1000
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+Epoch 18/1000
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+Epoch 19/1000
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+Epoch 20/1000
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+Epoch 21/1000
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+Epoch 22/1000
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+Epoch 23/1000
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+Epoch 24/1000
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+Epoch 25/1000
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+Epoch 26/1000
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+Epoch 27/1000
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+Epoch 28/1000
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+Epoch 29/1000
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+Epoch 30/1000
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+Epoch 31/1000
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+Epoch 32/1000
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+Epoch 33/1000
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+Epoch 34/1000
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+Epoch 35/1000
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+Epoch 36/1000
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+Epoch 37/1000
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+Epoch 38/1000
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+Epoch 39/1000
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+Epoch 40/1000
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+Epoch 41/1000
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+Epoch 42/1000
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+Epoch 43/1000
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+Epoch 44/1000
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+Epoch 45/1000
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+Epoch 46/1000
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+Epoch 47/1000
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+Epoch 48/1000
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+Epoch 49/1000
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+Epoch 50/1000
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+Epoch 51/1000
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+Epoch 52/1000
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+Epoch 53/1000
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+Epoch 54/1000
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+Epoch 57/1000
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+Epoch 58/1000
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+Epoch 59/1000
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+Epoch 63/1000
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+Epoch 64/1000
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+Epoch 65/1000
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+Epoch 79/1000
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+Epoch 82/1000
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+Epoch 83/1000
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+Epoch 87/1000
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+Epoch 88/1000
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+Epoch 91/1000
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+Epoch 93/1000
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+Epoch 94/1000
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+Epoch 95/1000
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+Epoch 96/1000
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+Epoch 97/1000
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+Epoch 121/1000
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+Epoch 122/1000
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+Epoch 123/1000
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+Epoch 126/1000
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+Epoch 137/1000
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+Epoch 140/1000
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+Epoch 141/1000
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+Epoch 142/1000
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+Epoch 143/1000
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+Epoch 146/1000
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+Epoch 184/1000
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+Epoch 185/1000
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+Epoch 186/1000
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+Epoch 187/1000
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+Epoch 188/1000
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+Epoch 189/1000
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+Epoch 190/1000
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+Epoch 192/1000
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+Epoch 193/1000
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+Epoch 195/1000
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+Epoch 196/1000
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+Epoch 197/1000
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+Epoch 199/1000
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+Epoch 203/1000
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+Epoch 204/1000
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+Epoch 205/1000
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+Epoch 206/1000
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+Epoch 207/1000
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+Epoch 208/1000
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+Epoch 211/1000
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+Epoch 213/1000
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+Epoch 214/1000
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+Epoch 216/1000
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+Epoch 217/1000
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+Epoch 219/1000
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+Epoch 220/1000
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+Epoch 222/1000
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+Epoch 225/1000
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+Epoch 245/1000
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+Epoch 248/1000
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+Epoch 249/1000
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+Epoch 255/1000
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+Epoch 256/1000
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+Epoch 258/1000
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+Epoch 268/1000
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+Epoch 269/1000
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+Epoch 271/1000
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+Epoch 273/1000
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+Epoch 354/1000
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+Epoch 357/1000
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+Epoch 359/1000
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+Epoch 362/1000
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+Epoch 379/1000
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+Epoch 399/1000
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+Epoch 401/1000
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+Epoch 404/1000
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+Epoch 409/1000
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+Epoch 415/1000
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+Epoch 416/1000
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+Epoch 417/1000
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+Epoch 418/1000
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+Epoch 419/1000
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+Epoch 420/1000
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+Epoch 421/1000
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+Epoch 422/1000
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+Epoch 425/1000
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+Epoch 426/1000
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+Epoch 431/1000
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+Epoch 432/1000
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+Epoch 433/1000
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+Epoch 434/1000
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+Epoch 436/1000
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+Epoch 439/1000
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+Epoch 441/1000
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+Epoch 443/1000
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+Epoch 448/1000
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+Epoch 477/1000
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+Epoch 487/1000
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+Epoch 488/1000
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+Epoch 547/1000
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+Epoch 549/1000
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+Epoch 552/1000
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+Epoch 569/1000
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+Epoch 571/1000
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+Epoch 572/1000
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+Epoch 586/1000
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+Epoch 605/1000
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+Epoch 606/1000
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+Epoch 608/1000
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+Epoch 609/1000
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+Epoch 612/1000
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+Epoch 615/1000
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+Epoch 617/1000
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+Epoch 619/1000
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+Epoch 623/1000
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+Epoch 834/1000
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+Epoch 836/1000
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+Epoch 837/1000
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+Epoch 838/1000
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+Epoch 839/1000
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+Epoch 841/1000
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+Epoch 842/1000
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+Epoch 843/1000
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+Epoch 845/1000
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+Epoch 848/1000
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+Epoch 849/1000
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+Epoch 850/1000
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+Epoch 851/1000
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+Epoch 852/1000
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+Epoch 857/1000
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+Epoch 858/1000
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+Epoch 861/1000
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+Epoch 862/1000
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+Epoch 864/1000
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+Epoch 865/1000
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+Epoch 866/1000
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+Epoch 867/1000
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+Epoch 868/1000
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+Epoch 869/1000
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+Epoch 871/1000
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+Epoch 874/1000
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+Epoch 875/1000
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+Epoch 876/1000
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+Epoch 877/1000
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+Epoch 878/1000
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+Epoch 879/1000
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+Epoch 880/1000
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+Epoch 881/1000
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+Epoch 883/1000
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+Epoch 884/1000
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+Epoch 885/1000
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+Epoch 886/1000
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+Epoch 887/1000
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+Epoch 888/1000
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+Epoch 889/1000
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+Epoch 890/1000
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+Epoch 891/1000
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+Epoch 892/1000
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+Epoch 893/1000
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+Epoch 894/1000
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+Epoch 896/1000
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+Epoch 897/1000
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+Epoch 898/1000
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+Epoch 899/1000
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+Epoch 903/1000
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+Epoch 905/1000
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+Epoch 906/1000
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+Epoch 907/1000
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+Epoch 908/1000
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+Epoch 909/1000
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+Epoch 910/1000
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+Epoch 911/1000
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+Epoch 912/1000
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+Epoch 913/1000
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+Epoch 914/1000
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+Epoch 916/1000
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+Epoch 917/1000
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+Epoch 918/1000
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+Epoch 919/1000
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+Epoch 920/1000
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+Epoch 921/1000
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+Epoch 922/1000
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+Epoch 923/1000
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+Epoch 924/1000
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+Epoch 925/1000
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+Epoch 926/1000
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+Epoch 927/1000
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+Epoch 928/1000
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+Epoch 929/1000
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+Epoch 930/1000
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+Epoch 931/1000
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+Epoch 932/1000
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+Epoch 933/1000
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+Epoch 935/1000
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+Epoch 936/1000
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+Epoch 938/1000
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+Epoch 939/1000
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+Epoch 941/1000
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+Epoch 945/1000
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+Epoch 946/1000
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+Epoch 947/1000
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+Epoch 948/1000
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+Epoch 949/1000
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+Epoch 950/1000
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+Epoch 951/1000
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+Epoch 952/1000
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+Epoch 953/1000
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+Epoch 954/1000
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+Epoch 955/1000
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+Epoch 958/1000
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+Epoch 959/1000
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+Epoch 960/1000
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+Epoch 961/1000
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+Epoch 964/1000
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+Epoch 965/1000
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+Epoch 966/1000
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+Epoch 967/1000
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+Epoch 968/1000
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+Epoch 969/1000
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+Epoch 970/1000
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+Epoch 972/1000
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+Epoch 973/1000
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+Epoch 974/1000
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+Epoch 975/1000
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+Epoch 976/1000
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+Epoch 977/1000
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+Epoch 978/1000
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+Epoch 979/1000
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+Epoch 980/1000
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+Epoch 981/1000
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+Epoch 982/1000
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+Epoch 983/1000
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+Epoch 984/1000
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+Epoch 985/1000
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+Epoch 986/1000
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+Epoch 987/1000
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+Epoch 988/1000
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+Epoch 989/1000
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+Epoch 990/1000
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+Epoch 991/1000
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+Epoch 992/1000
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+Epoch 993/1000
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+Epoch 994/1000
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+Epoch 995/1000
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+Epoch 996/1000
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+Epoch 997/1000
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+Epoch 998/1000
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+Epoch 999/1000
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+Epoch 1000/1000
+15/15 [==============================] - 0s 3ms/step - loss: 0.1033 - accuracy: 0.9560
+<keras.callbacks.History at 0x7fecba804b90>
+
+model.evaluate(x_test,y_test)
+
+WARNING:tensorflow:Model was constructed with shape (None, 455, 30) for input KerasTensor(type_spec=TensorSpec(shape=(None, 455, 30), dtype=tf.float32, name='dense_input'), name='dense_input', description="created by layer 'dense_input'"), but it was called on an input with incompatible shape (None, 30).
+4/4 [==============================] - 0s 4ms/step - loss: 0.0916 - accuracy: 0.9561
+[0.09155242145061493, 0.9561403393745422]