v0.6.0

Added

• Add changelog.md for the next releases (#ee44ac9).
• Add changelog.md and readme.md to each build of a release (#ee44ac9).
• Add for each target programming language a new new command-line argument (e.g. --java, --c or --go) (#41b93a0).
• Add argument --class_name and --method_name to define the class and method name in the final output directly (#6f2a1d9).
• Add pipe functionality and the related command-line argument (--pipe or -p) (#8a57746).
• Add --export argument to dump the model data and use the specific templates (#0669645).
• Add --checksum argument to append the computed md5 checksum at the end of the dumped model data file (#cd12827).
• Add --data argument to kust export the model data (#fad499a).
• Add test class Go in tests/language/Go.py to test all implementations for the target programming language Go (#1d0b5d6).
• Add Go compiling (go build -o brain brain.go) and execution (./brain) command (#5d24f57).
• Add initial Web Workers features in JavaScript templates (#87d3236) and a create seperate example (#187efac).
• Add the feature to read the estimator from a used Pipeline (#b92edff, issue: #18).
• Add a new class argument (num_format=lambda x: str(x)) to change the default representation of floating-point values (#7f9fac8).
• Use estimator name as default class name (e.g. MLPClasifier, KNeighborsClassifier, SVC, ...) (#710a854).
• Add new estimator:
  • Go:
    • tree.DecisionTreeClassifier (#fe59710)
  • JavaScript:
    • naive_bayes.BernoulliNB (#9784d6b)
  • PHP:
    • ensemble.RandomForestClassifier (#faac38d)
    • ensemble.ExtraTreesClassifier (#2a29321)
  • Ruby:
    • svm.SVC (#3ef1646)
    • svm.NuSVC (#0a39aaf)
    • tree.DecisionTreeClassifier (#a404c4f)
    • ensemble.RandomForestClassifier (#3775501)
    • ensemble.ExtraTreesClassifier (#81b9914)
• Add support to export and import model data:
  • Java:
    • svm.SVC notebook (#e753252)
    • svm.NuSVC notebook (#e753252)
    • svm.LinearSVC notebook (#562ed8c)
    • ensemble.AdaBoostClassifier notebook (#79d846f)
    • ensemble.RandomForestClassifier notebook (#9979a94)
    • ensemble.ExtraTreesClassifier notebook (#9979a94)
    • tree.DecisionTreeClassifier notebook (#9979a94)
    • neighbors.KNeighborsClassifier notebook (#1b81d3f)
    • naive_bayes.GaussianNB notebook (#b68c5df)
    • naive_bayes.BernoulliNB notebook (#7eae57d)
    • neural_network.MLPClassifier notebook (#b988f57, #d8ff774)
  • JavaScript:
    • ensemble.AdaBoostClassifier notebook (#9fdcc49, #dd70ac7, #2401fba)
    • neighbors.KNeighborsClassifier notebook (#f915b70)
    • neural_network.MLPClassifier notebook (#ce23148)
• Add new recipes:
  • JavaScript:
    • MLPClassifier Web Workers (#187efac)

Changed

• Use human-readable placeholders (e.g. '{class_name}.{method_name}') instead of index-based placeholders (e.g. '{0}.{1}') in all main templates of all estimators (#de02795).
• Change the order of optional and required arguments in the --help text (#54d9973).
• Change the default representation of floating-point values from repr(x) to str(x) (#7f9fac8).
• Use the method name integrity_score(X) instead of predict_test(X) to avoid misconceptions for the integrity test (#715ec7d).
• Separate the model data from the algorithm:
  • tree.DecisionTreeClassifier (#f669aab, #bba6296, #b727186, #e2740fd, #5c9da8a)
  • neighbors.KNeighborsClassifier (#59a0e91, #1ac5d8a)
  • neural_network.MLPClassifier (#635da46, #7d31668, #78296e2, #4cdcfde, #7820508, #7820508)
  • neural_network.MLPRegressor (#60d9d42, #e4a8169)
  • naive_bayes.GaussianNB (#1ac5d8a)
  • naive_bayes.BernoulliNB (#ff82bb8, #3c57a06)
  • svm.SVC and svm.NuSVC (#4745d8b, #5f77e4d, #59831da, #cd8f52e, #c483d25)
  • svm.LinearSVC (#bb617c7)

Removed

• Hide the command-line argument --language and -l for the choice of the target programming language (#fc14a3b).

Fixed

• Fix inaccuracies in neural_network.MLPRegressor and neural_network.MLPClassifier occurred by the transpiled tanh and identity activation functions (#6696410).
• Fix installation problems with pip and Python 3 (#2935828, issue: #17)
• Fix dynamic class name in the MLPClassifier template (#b988f57)