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Model #2

Model Type: MLP NN

Model Name: Classification task?

Model Inputs

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Model Inference

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Network Layers

Overview

2input
(linear)

~>

6hidden 1
(tanh)

~>

8output
(tanh)

Detail View

input layer

Activation:

2 nodes

#4001

out: 5.739

#4002

out: 5.060

edge 1 - 2

2 × 6 ~> 12 weights

hidden layer 1

Activation:

6 nodes

#4003

in: 1.568

bias: -0.173

out: 13.452

factor: 21.096

#4004

in: 1.964

bias: 0.398

out: 9.884

factor: 19.408

#4005

in: 2.147

bias: 0.302

out: 15.593

factor: 33.480

#4006

in: 2.164

bias: 0.115

out: 9.308

factor: 20.147

#4007

in: 0.361

bias: 0.246

out: 13.457

factor: 4.855

#4008

in: 2.594

bias: 0.193

out: 9.285

factor: 24.088

edge 2 - 3

6 × 8 ~> 48 weights

output layer

Activation:

8 nodes

#4009

in: 4.966

bias: -0.618

#4010

in: 13.573

bias: -4.016

#4011

in: 9.970

bias: -4.290

#4012

in: 9.260

bias: 1.276

#4013

in: 8.558

bias: 0.581

#4014

in: 8.520

bias: 0.064

#4015

in: 7.741

bias: -0.271

#4016

in: 8.391

bias: 0.338

Model Training

Trained 340 epoch

Learning Rate: Epoch to train:

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Dataset #2

Used by 3 model(s)

Dataset Name: Classification task?

Data Features

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Sample Data

Data Samples: 1,000

Feature Name: height (cm)

Min: 71

Avg: 171.928

Max: 219

Feature Name: weight (kg)

Min: 20

Avg: 93.707

Max: 219

Labels:

Label	Occurrence
severely underweight	120
moderately underweight	22
mildly underweight	37
normal	157
overweight	144
obese (Class I)	134
obese (Class II)	108
obese (Class III)	278