ANN MACD (BTC)

2019年10月2日

Logic is correct.
But I prefer to say experimental because the sample set is narrow. (300 columns)

Let's start:

6 inputs : Volume Change , Bollinger Low Band chg. , Bollinger Mid Band chg., Bollinger Up Band chg. , RSI change , MACD histogram change.
1 output : Future bar change (Historical)
Training timeframe : 15 mins (Analysis TF > 4 hours (My opinion))
Learning cycles : 337
Training error: 0.009999

Input columns: 6
Output columns: 1
Excluded columns: 0

Grid

Training example rows: 301
Validating example rows: 0
Querying example rows: 0
Excluded example rows: 0
Duplicated example rows: 0

Network

Input nodes connected: 6

Hidden layer 1 nodes: 8
Hidden layer 2 nodes: 0
Hidden layer 3 nodes: 0

Output nodes: 1

Learning rate : 0.6 Momentum : 0.8

More info :

EDIT : This code is open source under the MIT License. If you have any improvements or corrections to suggest, please send me a pull request via the github repository github.com/user-Noldo