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Diffstat (limited to 'README.md')
| -rw-r--r-- | README.md | 21 |
1 files changed, 11 insertions, 10 deletions
@@ -31,22 +31,23 @@ REST operations [feature_type=trees], [nr_hits=false] Create lazar model POST /lazar dataset_uri, URI for lazar model 200,400,404,500 - prediction_feature, - feature_generation_uri - prediction_algorithm - [local_svm_kernel=weighted_tanimoto] - [min_sim=0.3] - [nr_hits=false] - [conf_stdev=false] + [prediction_feature], + [feature_generation_uri], + [prediction_algorithm], + [feature_dataset_uri], + [propositionalized=false], + [pc_type=null], + [nr_hits=false (class.), true (regr.)], + [min_sim=0.3 (nominal), 0.6 (numeric features)] Synopsis -------- - prediction\_algorithm: One of "weighted\_majority\_vote" (default for classification), "local\_svm\_classification", "local\_svm\_regression (default for regression)", "local\_mlr\_prop". "weighted\_majority\_vote" is not applicable for regression. "local\_mlr\_prop" is not applicable for classification. -- local\_svm\_kernel: One of "weighted\_tanimoto", "propositionalized". local\_svm\_kernel is not appplicable when prediction\_algorithm="weighted\_majority\_vote". -- min_sim: The minimum similarity threshold for neighbors. Numeric value in [0,1]. +- propositionalized: One of "true", "false". Not appplicable when prediction\_algorithm="weighted\_majority\_vote". +- pc_type: Mandatory for feature dataset, one of [geometrical, topological, electronic, constitutional, hybrid, cpsa]. - nr_hits: Whether for instantiated models (local\_svm\_kernel = "propositionalized" for prediction_algorithm="local\_svm\_classification" or "local\_svm\_regression", or for prediction_algorithm="local\_mlr\_prop") nominal features should be instantiated with their occurrence counts in the instances. For non-instantiated models (local\_svm\_kernel = "weighted\_tanimoto" for prediction_algorithm="local\_svm\_classification" or "local\_svm\_regression", or for prediction_algorithm="weighted\_majority\_vote") the neighbor-to-neighbor and neighbor-to-query similarity also integrates these counts, when the parameter is set. One of "true", "false". -- conf_stdev: Whether confidence integrates distribution of neighbor activity values. When "true", the exp(-1.0*(standard deviation of neighbor activities)) is multiplied on the similarity. One of "true", "false". +- min_sim: The minimum similarity threshold for neighbors. Numeric value in [0,1]. See http://www.maunz.de/wordpress/opentox/2011/lazar-models-and-how-to-trigger-them for a graphical overview. |