import pandas as pd
from pathlib import Path
import tensorflow as tf
from tensorflow.keras.layers import Dense
from tensorflow.keras.models import Sequential
from sklearn.model_selection import train_test_split
from sklearn.preprocessing import StandardScaler,OneHotEncoder
Original Model: Hidden layer 1: 16, relu Hidden layer 2: 12, relu Output layer: linear Loss: 0.6414 Accuracy: 0.7284
Alternative Model 1: Hidden layer 1: 28, relu Hidden layer 2: 8, relu Output layer: linear Loss: 0.6249 Accuracy: 0.7280
Alternative Model 2: Hidden layer 1: 40, relu Hidden layer 2: 14, relu Output layer: linear Loss: 0.6025 Accuracy: 0.7268
This Analysis is brought to you by billybishop21
MIT License
Copyright (c) 2021 billybishop21
Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions:
The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software.
THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.