| DecisionTree__apply_prepruning | Activates the pre pruning and delivers a prepruned tree. | default: true |
| DecisionTree__apply_pruning | Activates the pruning of the tree. | default: true |
| DecisionTree__confidence | The confidence level used for the pessimistic error calculation of pruning. | default: 0.25 |
| DecisionTree__criterion | Specifies the used criterion for selecting attributes and numerical splits. | default: gain_ratio |
| DecisionTree__maximal_depth | The maximum tree depth (-1: no bound) | default: 20 |
| DecisionTree__minimal_gain | The minimal gain which must be achieved in order to produce a split. | default: 0.1 |
| DecisionTree__minimal_leaf_size | The minimal size of all leaves. | default: 2 |
| DecisionTree__minimal_size_for_split | The minimal size of a node in order to allow a split. | default: 4 |
| DecisionTree__number_of_prepruning_alternatives | The number of alternative nodes tried when prepruning would prevent a split. | default: 3 |
| Normalize__allow_negative_values | Whether negative values should be allowed and used as absolute values | default: false |
| Normalize__attribute | The attribute which should be chosen. | |
| Normalize__attribute_filter_type | The condition specifies which attributes are selected or affected by this operator. | default: all |
| Normalize__attributes | The attribute which should be chosen. | |
| Normalize__block_type | The block type of the attributes. | default: value_series |
| Normalize__create_view | Create View to apply preprocessing instead of changing the data | default: false |
| Normalize__except_block_type | Except this block type. | default: value_series_end |
| Normalize__except_regular_expression | A regular expression for the names of the attributes which should be filtered out although matching the above regular expression. | |
| Normalize__except_value_type | Except this value type. | default: real |
| Normalize__include_special_attributes | Indicate if this operator should also be applied on the special attributes. Otherwise they are always kept. | default: false |
| Normalize__invert_selection | Indicates if only attributes should be accepted which would normally filtered. | default: false |
| Normalize__max | The maximum value after normalization | default: 1.0 |
| Normalize__method | Select the normalization method. | default: Z-transformation |
| Normalize__min | The minimum value after normalization | default: 0.0 |
| Normalize__numeric_condition | Parameter string for the condition, e.g. '>= 5' | |
| Normalize__regular_expression | A regular expression for the names of the attributes which should be kept. | |
| Normalize__return_preprocessing_model | Indicates if the preprocessing model should also be returned | default: false |
| Normalize__use_block_type_exception | If enabled, an exception to the specified block type might be specified. | default: false |
| Normalize__use_except_expression | If enabled, an exception to the specified regular expression might be specified. Attributes of matching this will be filtered out, although matching the first expression. | default: false |
| Normalize__use_value_type_exception | If enabled, an exception to the specified value type might be specified. Attributes of this type will be filtered out, although matching the first specified type. | default: false |
| Normalize__value_type | The value type of the attributes. | default: numeric |
| Store__repository_entry | Repository entry. | |