Ensemble Machine Learning Trader implements an ensemble approach, combining predictions from Logistic Regression, Support Vector Machines, Random Forest, and XGBoost. The system operates in two primary modes: technical indicator analysis and macroeconomic news-driven execution. It manages risk through fixed stop loss and take profit points. Users can configure model agreement thresholds and filter trades based on the scheduled impact of economic news events.
Read from EnsembleOnnxTrader.mq5. Defaults are the author's; change them in the EA's Inputs tab.
Name
Type
Default
Description
InpModelFolder
string
EnsembleOnnxTrader
InpSignalSource
ENUM_SIGNAL_SOURCE
SIGNAL_ENSEMBLE
InpLots
double
0.10
InpSlPoints
int
300
InpTpPoints
int
600
InpUseCommonFiles
bool
true
InpUseCpuOnly
bool
true
InpCloseOnHold
bool
false
InpMagicNumber
ulong
26072401
InpCooldownBars
int
12
InpMinSignalEdge
double
0.03
InpMinAgreementVotes
int
2
Show all 18 inputs
Name
Type
Default
Description
InpEnableTransactionCsv
bool
true
InpTransactionCsvFile
string
InpExportHistoryOnDeinit
bool
true
InpUseNewsFilter
bool
true
InpNewsCsvFile
string
Assets\\MT5_2018.01.01-2026.06.30_ALL_.csv
InpNewsMinImpact
int
0
How to install it
1Download the sourceUse "Download source (.zip)" above, or clone dillahbaraja/Ensemble_ML from GitHub, and unzip it.
2Open the data folderIn MetaTrader choose File, then Open Data Folder, and go to MQL5/Experts.
3Copy the filesCopy the .mq5 file into Experts.
4Compile in MetaEditorOpen the file in MetaEditor and press Compile. Fix any missing includes the compiler reports.
5Test before you tradeRun it in the Strategy Tester, then attach it to a demo chart and allow algorithmic trading.
Third-party code. ForexR did not write, test or endorse this EA, and the summary above was generated automatically from its README and code. ForexR lists only repositories with readable source code and never hosts files. Read the code, backtest it and use a demo account first; automated trading can lose money quickly.
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