Create JSON files that have the default parameter grid to explore

[Y-oHr-N]

See below

• TPOT
• auto-sklearn
• hyperopt-sklearn
• auto_ml

[Y-oHr-N]

'FastABOD': {
    'n_neighbors': randint(3, 101),
    'p': [1, 2],
    'contamination': uniform(0.05, 0.15)
}

[Y-oHr-N]

'LOF': {
    'n_neighbors': randint(1, 101),
    'p': [1, 2],
    'contamination': 'auto' # original paper
}

[Y-oHr-N]

'KNN': {
    'n_neighbors': randint(1, 101),
    'p': [1, 2],
    'contamination': uniform(0.05, 0.15)
}

[Y-oHr-N]

OneTimeSampling: {
    'max_samples': [20], # original paper
    'p': [1, 2],
    'contamination': uniform(0.05, 0.15)
}

[Y-oHr-N]

HBOS: {
    'bins': 'auto',
    'contamination': uniform(0.05, 0.15)
}

[Y-oHr-N]

SVDD: {
}

[Y-oHr-N]

MiniBatchKMeans: {
}

[Y-oHr-N]

'IForest': {
    'n_estimators': [100], # original paper
    'max_features': uniform(0.05, 0.95),
    'max_samples': 'auto', # original paper
    'bootstrap': [True, False],
    'contamination': 'auto' # original paper
}

[Y-oHr-N]

PCA: {
}

[Y-oHr-N]

GMM: {
}

[Y-oHr-N]

KDE: {
}

[Y-oHr-N]

SparseStructureLearning: {
}