| Analytical Function Name | New arguments | Argument type change numeric → integer | Argument default value update | Argument Optional ↔ Required |
|---|---|---|---|---|
| MLE Functions | ||||
| td_adaboost_mle | iter.num, num.splits, max.depth, min.node.size | |||
| td_antiselect_mle | data.order.column | |||
| td_arima_mle | period, max.iterations, order.p, order.d, order.q, seasonal.order.p, seasonal.order.d, seasonal.order.q | |||
| td_arima_predict_mle | n.ahead | |||
| td_burst_mle | num.points, seed | The argument "time.data.partition.column" was required. Now, it is required when the argument "time.data" is provided; optional otherwise. | ||
| td_ccm_mle | embedding.dimension, time.step, bootstrap.iterations, predict.step, library.size | |||
| td_ccm_prepare_mle | data.order.column | data.partition.column: NULL → "1" | ||
| td_cfilter_mle | max.itemset | |||
| td_changepoint_detection_mle | max.change.num | |||
| td_changepoint_detection_rt_mle | window.size | The argument "accumulate" was required. It is optional now. | ||
| td_confusion_matrix_mle | data.sequence.column | |||
| td_cox_hazard_ratio_mle | object.order.column, predicts.order.column, refs.order.column | predicts.partition.column: NULL → "1", refs.partition.column: NULL → "1" | ||
| td_coxph_mle | max.iter.num | |||
| td_decision_forest_evaluator_mle | object.order.column | |||
| td_decision_forest_mle | maxnum.categorical, ntree, tree.size, nodesize, max.depth, mtry | |||
| td_decision_tree_mle | num.splits, nodesize, max.depth | |||
| td_dtw_mle | radius | |||
| td_dwt2d_mle | level | |||
| td_dwt_mle | level | |||
| td_exponential_mov_avg_mle | start.rows | |||
| td_fpgrowth_mle | group.size | |||
| td_glm_mle | maxit | |||
| td_glml1l2_mle | max.iter.num | |||
| td_hmm_decoder_mle | init.state.prob.order.column, state.transition.prob.order.column, emission.prob.order.column | sequence.max.size | ||
| td_hmm_evaluator_mle | init.state.prob.order.column, state.transition.prob.order.column, emission.prob.order.column | |||
| td_hmm_supervised_mle | batch.size | The argument "model.key" was required. It is optional now. | ||
| td_hmm_unsupervised_mle | hidden.states.num, max.iter.num | The argument "model.key" was required. It is optional now. | ||
| td_kmeans_mle | iter.max, seed | |||
| td_knn_mle | k, parblock.size | |||
| td_knn_recommender_mle | k, max.iternum | |||
| td_knn_recommender_predict_mle | showall, ratings.data.order.column, weights.data.order.column, bias.data.order.column | topk | ||
| td_lar_mle | max.steps | |||
| td_lar_predict_mle | newdata.order.column, object.order.column | |||
| td_lda_mle | topic.num, count.column, initmodeltaskcount | |||
| td_levenshtein_distance_mle | threshold | |||
| td_lin_reg_mle | data.order.column | |||
| td_linreg_predict_mle | newdata.order.column, object.order.column | |||
| td_minhash_mle | hash.num, key.groups, mincluster.size, maxcluster.size | |||
| td_naivebayes_mle | data.sequence.column, data.order.column | |||
| td_naivebayes_textclassifier_mle | data.order.column, stopwords.data.order.column, categories.data.order.column | |||
| td_naivebayes_textclassifier_predict_mle | top.k | |||
| td_namedentity_finder_evaluator_mle | newdata.order.column | |||
| td_namedentity_finder_mle | newdata.order.column, configure.table.data.order.column | show.entity.context | ||
| td_namedentity_finder_trainer_mle | iter.num, cutoff | |||
| td_ngramsplitter_mle | data.sequence.column, data.order.column | |||
| td_npath_mle | data1.sequence.column, data2.sequence.column, data3.sequence.column | The argument "data2.order.column" was required. Now, it is required when the argument "data2" is provided; optional otherwise. The argument "data3.order.column" was required. Now, it is required when the argument "data3" is provided; optional otherwise. | ||
| td_ntree_mle | max.distance | |||
| td_pack_mle | data.sequence.column, data.order.column | |||
| td_page_rank_mle | niter | |||
| td_pivot_mle | num.rows | |||
| td_random_sample_mle | num.sample, iteration.num | over.sampling.rate: 1 → 1.0 | ||
| td_sampling_mle | approx.sample.size | seed: NULL → 0 | ||
| td_sax_mle | window.size, output.frequency, points.persymbol, symbols.perwindow, alphabet.size, bitmap.level | The argument "meanstats.data.partition.column" was required. Now, it is required when the argument "meanstats.data" is provided; optional otherwise. | ||
| td_scale_by_partition_mle | data.order.column | |||
| td_scale_map_mle | data.order.column | |||
| td_scale_mle | data.order.column, object.order.column | |||
| td_scale_summary_mle | object.order.column | |||
| td_sentence_extractor_mle | data.order.column | |||
| td_sentiment_evaluator_mle | object.order.column | |||
| td_sentiment_extractor_mle | newdata.order.column, dict.data.order.column | |||
| td_simple_mov_avg_mle | window.size | |||
| td_string_similarity_mle | data.order.column | |||
| td_svm_dense_mle | degree, hash.bits, max.step, subspace.dimension | cost: 1 → 1.0 | ||
| td_svm_dense_predict_mle | output.class.num | |||
| td_svm_dense_summary_mle | data.order.column, object.order.column | |||
| td_svm_sparse_mle | hash.buckets, max.step | cost: 1 → 1.0 | ||
| td_svm_sparse_predict_mle | output.class.num | |||
| td_svm_sparse_summary_mle | data.sequence.column, object.sequence.column, data.order.column, object.order.column | |||
| td_text_parser_mle | data.sequence.column, data.order.column | |||
| td_text_tagger_mle | data.order.column, rules.data.order.column | |||
| td_text_tokenizer_mle | data.sequence.column, dict.data.sequence.column, data.order.column, dict.data.order.column | |||
| td_unpack_mle | data.sequence.column, data.order.column | regex.set | ||
| td_unpivot_mle | data.order.column | |||
| td_varmax_mle | period, exogenous.order, lag, max.iter.num, step.ahead, order.p, order.d, order.q, seasonal.order.p, seasonal.order.d, seasonal.order.q | |||
| td_vector_distance_mle | top.k | |||
| td_weighted_mov_avg_mle | window.size | |||
| td_xgboost_mle | iter.num, min.node.size, max.depth, num.boosted.trees | |||
| td_xgboost_predict_mle | iter.num, num.boosted.trees | |||
| SQLE Functions | ||||
| td_attribution_sqle | The argument "data.optional.partition.column" was required. Now, it is required when the argument "data.optional" is provided; optional otherwise. The argument "data.optional.order.column" was required. Now, it is required when the argument "data.optional" is provided; optional otherwise. | |||
| td_decision_forest_predict_sqle | newdata.order.column, object.order.column | |||
| td_decision_tree_predict_sqle | object.order.column | |||
| td_glm_predict_sqle | newdata.order.column | |||
| td_moving_average_sqle | window.size, start.rows | |||
| td_naivebayes_predict_sqle | newdata.order.column, modeldata.order.column | |||
| td_naivebayes_textclassifier_predict_sqle | newdata.order.column, object.order.column | top.k | ||
| td_npath_sqle | The argument "data2.order.column" was required. Now, it is required when the argument "data2" is provided; optional otherwise. The argument "data3.order.column" was required. Now, it is required when the argument "quot;data3" is provided; optional otherwise. | |||
| td_svm_sparse_predict_sqle | newdata.order.column, object.order.column | output.class.num | ||
| td_unpack_sqle | regex.set | |||
Note: Whenever there is an update to any predict function (like |