数据科学和机器学习（第 38 部分）：外汇市场中的 AI 迁移学习（基础篇）

class="macro">#include <pandas.mqh> class=class="str">"cmt">//[MQL5官方文档]
input class="type">class="kw">datetime start_date = D&class="macro">#x27;class="num">2005.01.class="num">01&class="macro">#x27;;
input class="type">class="kw">datetime end_date = D&class="macro">#x27;class="num">2023.01.class="num">01&class="macro">#x27;;
input class="type">class="kw">string symbols = "EURUSD|GBPUSD|AUDUSD|USDCAD|USDJPY|USDCHF|NZDUSD|EURNZD|AUDNZD|GBPNZD|NZDCHF|NZDJPY|NZDCAD|XAUUSD|XAUJPY|XAUEUR|XAUGBP";
input ENUM_TIMEFRAMES timeframe = PERIOD_D1;
class=class="str">"cmt">//+------------------------------------------------------------------+
class=class="str">"cmt">//| Script program start function                                    |
class=class="str">"cmt">//+------------------------------------------------------------------+
class="type">void OnStart()
  {
   class="type">class="kw">string SymbolsArr[];
   class="type">class="kw">ushort sep = StringGetCharacter("|",class="num">0);
   if (StringSplit(symbols, sep, SymbolsArr)<class="num">0)
     {
      printf("%s failed to split the symbols, Error %d",__FUNCTION__,GetLastError());
      class="kw">return;
     }
   
class=class="str">"cmt">//---

   vector open, high, low, close;
   for (class="type">uint i=class="num">0; i<SymbolsArr.Size(); i++)
    {
     class="type">class="kw">string symbol = SymbolsArr[i];
     if (!SymbolSelect(symbol, true))
       {
        printf("%s failed to select symbol %s, Error = %d",__FUNCTION__,symbol,GetLastError());
        class="kw">continue;
       }

     class=class="str">"cmt">//---

     open.CopyRates(symbol, timeframe, COPY_RATES_OPEN, start_date, end_date);
     high.CopyRates(symbol, timeframe, COPY_RATES_HIGH, start_date, end_date);
     low.CopyRates(symbol, timeframe, COPY_RATES_LOW, start_date, end_date);
     close.CopyRates(symbol, timeframe, COPY_RATES_CLOSE, start_date, end_date);

     CDataFrame df;
     
     df.insert("Open", open);
     df.insert("High", high);
     df.insert("Low", low);
     df.insert("Close", close);
     
     df.to_csv(StringFormat("Fxdata.%s.%s.csv",symbol,EnumToString(timeframe)), true);
    }
  }
def getXandY(symbol: str, timeframe: str, lookahead: class="type">int) -> tuple:
    df = pd.read_csv(f"/kaggle/input/ohlc-eurusd/Fxdata.{symbol}.{timeframe}.csv")
    # Target variable
    df["future_close"] = df["Close"].shift(-lookahead)
    df.dropna(inplace=True)
    

df["Signal"] = (df["future_close"] > df["Close"]).astype(class="type">int)

# Splitting data into X and y
X = df.drop(columns=[
    "future_close",
    "Signal"
])
y = df["Signal"]
class="kw">return (X, y)
def trainSymbol(X_train: pd.DataFrame, y_train: pd.DataFrame) -> Pipeline:

    # Training a model
    classifier = RandomForestClassifier(n_estimators=class="num">100, min_samples_split=class="num">3, max_depth = class="num">5)
    pipeline = Pipeline([
        ("scaler", RobustScaler()),
        ("classifier", classifier)
    ])
    pipeline.fit(X_train, y_train)
    class="kw">return pipeline
def evalSymbol(model: Pipeline, X: pd.DataFrame , y: pd.Series) -> class="type">int:

    # evaluating the model
    preds = model.predict(X)
    acc = accuracy_score(y, preds)

    class="kw">return acc
symbols = ["EURUSD","GBPUSD","AUDUSD","USDCAD","USDJPY","USDCHF","NZDUSD","EURNZD","AUDNZD","GBPNZD","NZDCHF","NZDJPY","NZDCAD","XAUUSD","XAUJPY","XAUEUR","XAUGBP"]
# training on EURUSD
lookahead = class="num">1
X, y = getXandY(symbol=symbols[class="num">0], timeframe="PERIOD_H4", lookahead=lookahead)
X_train, X_test, y_train, y_test = train_test_split(X, y, random_state=class="num">42, shuffle=True)
model = trainSymbol(X_train, y_train)
# Evaluating on the rest of symbols
trained_symbol = symbols[class="num">0]
print(f"Trained on {trained_symbol}")
for symbol in symbols:
    X, y = getXandY(symbol=symbol, timeframe="PERIOD_H4", lookahead=class="num">1)

    acc = evalSymbol(model, X, y)    
    print(f"--> {symbol} | acc: {acc}")
Trained on EURUSD
--> EURUSD | acc: class="num">0.5478518727715607
--> GBPUSD | acc: class="num">0.5009182736455464
--> AUDUSD | acc: class="num">0.5026133634694165
--> USDCAD | acc: class="num">0.4973701860284514
--> USDJPY | acc: class="num">0.49477401129943505
--> USDCHF | acc: class="num">0.5078731817539895
--> NZDUSD | acc: class="num">0.4976826463824518
--> EURNZD | acc: class="num">0.5071507150715071
--> AUDNZD | acc: class="num">0.5005597760895641
--> GBPNZD | acc: class="num">0.503459397596629
--> NZDCHF | acc: class="num">0.4990389436737423
--> NZDJPY | acc: class="num">0.4908841561794127
--> NZDCAD | acc: class="num">0.5023507681974645
--> XAUUSD | acc: class="num">0.48674396277970605
--> XAUJPY | acc: class="num">0.4816082121471343
--> XAUEUR | acc: class="num">0.4925268155442237
--> XAUGBP | acc: class="num">0.49455864570737607