Closed exalate-issue-sync[bot] closed 1 year ago
Neeraja Madabhushi commented: Also duration in MS and scoring time shows as 0
Neeraja Madabhushi commented: GBM output also shows nothing and the scoring/duration times shows as 0
Neeraja Madabhushi commented: Same with GLM, please check attachment.
Arno Candel commented: DL output is all expected - it's not an error.
variable_importances = false validation_frame = NULL export_weights_and_biases = false
=>
variable importance, validation metrics, weights, biases its all empty.
However, duration and scoring time are 0, we are aware of that.
Also, Tomas still needs to add GLM model summary and scoring history for GLM, and maybe also variable_importances, not sure.
Neeraja Madabhushi commented: Get that variable importance/validation frame and export weights are not specified during build model.
We should give some message stating that instead of showing blanks for them.
JIRA Issue Migration Info
Jira Issue: PUBDEV-828 Assignee: Arno Candel Reporter: Neeraja Madabhushi State: Resolved Fix Version: N/A Attachments: Available (Count: 5) Development PRs: N/A
Attachments From Jira
Attachment Name: Screen Shot 2015-04-14 at 1.19.27 PM.png Attached By: Neeraja Madabhushi File Link:https://h2o-3-jira-github-migration.s3.amazonaws.com/PUBDEV-828/Screen Shot 2015-04-14 at 1.19.27 PM.png
Attachment Name: Screen Shot 2015-04-14 at 1.19.34 PM.png Attached By: Neeraja Madabhushi File Link:https://h2o-3-jira-github-migration.s3.amazonaws.com/PUBDEV-828/Screen Shot 2015-04-14 at 1.19.34 PM.png
Attachment Name: Screen Shot 2015-04-14 at 1.58.32 PM.png Attached By: Neeraja Madabhushi File Link:https://h2o-3-jira-github-migration.s3.amazonaws.com/PUBDEV-828/Screen Shot 2015-04-14 at 1.58.32 PM.png
Attachment Name: Screen Shot 2015-04-14 at 1.58.39 PM.png Attached By: Neeraja Madabhushi File Link:https://h2o-3-jira-github-migration.s3.amazonaws.com/PUBDEV-828/Screen Shot 2015-04-14 at 1.58.39 PM.png
Attachment Name: Screen Shot 2015-04-14 at 2.11.02 PM.png Attached By: Neeraja Madabhushi File Link:https://h2o-3-jira-github-migration.s3.amazonaws.com/PUBDEV-828/Screen Shot 2015-04-14 at 2.11.02 PM.png
Steps to reproduce :
1) H2o cluster on ec2 of 16 nodes build 1138 2) importFiles [ "s3n://h2o-datasets/covtype.data" ] 3) Parse 4) Build DL model buildModel 'deeplearning', {"destination_key":"deeplearning-fd61cc20-13b3-4ea8-98fd-bf7443032bcc","training_frame":"covtype.hex","dropNA20Cols":false,"response_column":"C55","activation":"Rectifier","hidden":[50,50],"epochs":"11","variable_importances":false,"balance_classes":false,"checkpoint":"","use_all_factor_levels":true,"train_samples_per_iteration":-2,"adaptive_rate":true,"input_dropout_ratio":0,"hidden_dropout_ratios":[],"l1":0,"l2":0,"loss":"Automatic","score_interval":5,"score_training_samples":10000,"score_validation_samples":0,"score_duty_cycle":0.1,"replicate_training_data":true,"autoencoder":false,"class_sampling_factors":[],"max_after_balance_size":5,"max_confusion_matrix_size":20,"max_hit_ratio_k":10,"keep_cross_validation_splits":false,"override_with_best_model":true,"target_ratio_comm_to_comp":0.02,"seed":-1206720737534959000,"rho":0.99,"epsilon":1e-8,"rate":0.005,"rate_annealing":0.000001,"rate_decay":1,"momentum_start":0,"momentum_ramp":1000000,"momentum_stable":0,"nesterov_accelerated_gradient":true,"max_w2":"Infinity","initial_weight_distribution":"UniformAdaptive","initial_weight_scale":1,"classification_stop":0,"regression_stop":0.000001,"score_validation_sampling":"Uniform","diagnostics":true,"fast_mode":true,"ignore_const_cols":true,"force_load_balance":true,"single_node_mode":false,"shuffle_training_data":false,"missing_values_handling":"MeanImputation","quiet_mode":false,"sparse":false,"col_major":false,"average_activation":0,"sparsity_beta":0,"max_categorical_features":2147483647,"reproducible":false,"export_weights_and_biases":false}
5) Predict 6) Check output section for variable importance, validation metrics, weights, biases its all empty.
Check attachments