docs: private SB toJavaPredict(SB ccsb, SB fileCtxSb) { // ccsb = classContext
      ccsb.nl();
      ccsb.p("  // Pass in data in a double[], pre-aligned to the Model's requirements.").nl();
      ccsb.p("  // Jam predictions into the preds[] array; preds[0] is reserved for the").nl();
      ccsb.p("  // main prediction (class for classifiers or value for regression),").nl();
      ccsb.p("  // and remaining columns hold a probability distribution for classifiers.").nl();
      ccsb.p("  public final float[] predict( double[] data, float[] preds) { preds = predict( data, preds, "+toJavaDefaultMaxIters()+"); return preds; }").nl();
  //    ccsb.p("  public final float[] predict( double[] data, float[] preds) { return predict( data, preds, "+toJavaDefaultMaxIters()+"); }").nl();
      ccsb.p("  public final float[] predict( double[] data, float[] preds, int maxIters ) {").nl();
      SB classCtxSb = new SB();
      toJavaPredictBody(ccsb.ii(1), classCtxSb, fileCtxSb); ccsb.di(1);
      ccsb.p("    return preds;").nl();
      ccsb.p("  }").nl();
      ccsb.p(classCtxSb);
      return ccsb;
    }