Persistence of gradient boosted trees solutions takes a long time and creates really big files

[gkronber]

The reasons are the same as for random forests (see #1721)

[gkronber]

r12868: introduced surrogate for GBT-models which recalculates the actual model on demand to improve persistence of GBT solutions

[gkronber]

r12873: derived ILossFunction from IItem to allow execution on hive without privileged flag (made an "after deserialization"-hook necessary to convert the parameter type)

[gkronber]

r12875: fixed constructors for loss functions

[mkommend]

Reviewed r12868, r12873, and r12875.

It is a good idea to save the algorithms parameterization instead of the whole model. However, I would remove usages of the GBTModel wherever possible (deprecate?). For example, GBTAlgorithmStatic.TrainGbm returns a GBTModel and no surrogate, which cannot be loaded anymore and is therefore useless.

[gkronber]

using System;
using System.Linq;
using System.Collections.Generic;

using HeuristicLab.Core;
using HeuristicLab.Common;

using HeuristicLab.Algorithms.DataAnalysis;
using HeuristicLab.Problems.DataAnalysis;

public class MyScript : HeuristicLab.Scripting.CSharpScriptBase {
  public override void Main() {
    // type your code here
    var data = (IRegressionProblemData)vars["problemData"];
    var model = GradientBoostedTreesAlgorithmStatic.TrainGbm(data, new SquaredErrorLoss(), 100, 0.1, 1, 1, 10);
    vars["model"] = model;
  }
}

[gkronber]

r13065:

• marked constructor of GBTModel obsolete
• wrapped GBTModels in GBTModelSurrogates where necessary in the API.
• Removed an internal unused method from the API.
• Removed explicit usage of GBTModelSurrogate in GBTAlgorithm because gbtState.GetModel() already returns the correct type.

Changes can be tested with above script and GBT algorithm in HeuristicLab.

1. Run the algorithm (either script or through GUI)
2. Store and load the solution from disk
3. Compare estimated values

[gkronber]

r13066: adapted unit test for r13065.

[mkommend]

Reviewed r13065 & r13066.

GradientBoostedTreesAlgorithmStatic.TrainGbm should return a GBT solution. SurrogateGBTModel should implement IGBTModel and forward calls to the actual Model. Remove getter for actual model from SurrogateGBT model. Adapt unit test accordingly.

[gkronber]

r13157: made the changes suggested by mkommend in the review. This is definitely a big improvement, thx!

[gkronber]

r13158: copy constructor fix

[mkommend]

Reviewed r13157 and r13158.

[gkronber]

r13184: merged r12868,r12873,r12875,r13065:13066,r13157:13158 from trunk to stable