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You will get robust and highly predictive ML perceptron and RBF neural network models
Project details
Artificial neural networks (ANNs) have proven to be an efficient alternative to traditional methods for mode ling qualitative and quantitative variables. In this Gig, I offer myself to construct neural networks architectures. The number of hidden nodes will be determined by systematically increasing the number of nodes from 1 to 12 until the network performance will not be improved any more. Many activation functions (tanh, logistic, exponential, sinh, identity) will be employed in both hidden and output units. The dataset will be divided into training, testing and validation parts. The developed models will be compared with each other by using widely employed error statistics. The related graphs will be plotted. Overtraining will be avoided.
What's included
| Service Tiers |
Starter
$40
|
Standard
$70
|
Advanced
$90
|
|---|---|---|---|
| Delivery Time | 1 day | 3 days | 5 days |
Number of Revisions | Unlimited | Unlimited | Unlimited |
Number of Model Variations | 200 | 500 | 1000 |
Model Validation/Testing | |||
Model Documentation | |||
Data Source Connectivity | - | - | - |
Source Code | - | - | - |
Frequently asked questions
About Jasna
Predictive Model Developer/ Statistician/ Data scientist
Delft, Netherlands - 3:42 am local time
Steps for completing your project
After purchasing the project, send requirements so Jasna can start the project.
Delivery time starts when Jasna receives requirements from you.
Jasna works on your project following the steps below.
Revisions may occur after the delivery date.
Step 1
Data collection
Step 2
Preprocessing data (data is divided into three parts as training 70%, testing 15%, and validation 15%. Later, dataset is normalized so that the distribution for each standardized feature is zero-mean and unit-variance).