by the Oracle Cloud Infrastructure
\n", "\n", "***\n", "\n", "## Overview:\n", "This notebook provides a sample Parkinsons classification technique using OCI's data science tools using one's uttered speech.\n", "\n", " \n", "\n", "It demonstrates simple steps for training a model and deploying it to production.\n", "\n", "---\n", "\n", "## Contents:\n", "\n", "* Introduction\n", " * Dataset\n", "* Exploratory Data Analysis (EDA)\n", " * Column Transformations\n", " * ADS Dataset Analysis\n", " * Pair Plots\n", " * Feature Scaling\n", " * Distribution of the Target Classes\n", " * Split Training and Testing datasets, and Separate Target Column\n", "* Model Selection\n", " * Compare Model performances\n", " * Model Selection with ADS AutoML\n", " * Custom ADSDataset Class\n", " * AutoML Setup\n", "* Explaining the Model\n", " * Show what the model has learned\n", " * Global Explanations\n", " * Feature Dependence Explanations (PDP & ICE)\n", " * What-if Scenarios\n", " * Prediction Explorer\n", " * Local Explanations\n", "* Model Deployment\n", " * Create a Serialized Model\n", " * Prepare the Model Artifacts\n", " * Verify: Test the Model Locally\n", " * Save the Model in the Model Catalog\n", " * Deploy\n", " * Predict\n", "* Invoking the Endpoint \n", "* Clean Up\n", "* References \n", "---\n", "\n", "**Important:**\n", "\n", "`database_name = \"| \n", " | name | \n", "MDVP:Fo(Hz) | \n", "MDVP:Fhi(Hz) | \n", "MDVP:Flo(Hz) | \n", "MDVP:Jitter(%) | \n", "MDVP:Jitter(Abs) | \n", "MDVP:RAP | \n", "MDVP:PPQ | \n", "Jitter:DDP | \n", "MDVP:Shimmer | \n", "... | \n", "Shimmer:DDA | \n", "NHR | \n", "HNR | \n", "status | \n", "RPDE | \n", "DFA | \n", "spread1 | \n", "spread2 | \n", "D2 | \n", "PPE | \n", "
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | \n", "phon_R01_S01_1 | \n", "119.992 | \n", "157.302 | \n", "74.997 | \n", "0.00784 | \n", "0.00007 | \n", "0.00370 | \n", "0.00554 | \n", "0.01109 | \n", "0.04374 | \n", "... | \n", "0.06545 | \n", "0.02211 | \n", "21.033 | \n", "1 | \n", "0.414783 | \n", "0.815285 | \n", "-4.813031 | \n", "0.266482 | \n", "2.301442 | \n", "0.284654 | \n", "
| 1 | \n", "phon_R01_S01_2 | \n", "122.400 | \n", "148.650 | \n", "113.819 | \n", "0.00968 | \n", "0.00008 | \n", "0.00465 | \n", "0.00696 | \n", "0.01394 | \n", "0.06134 | \n", "... | \n", "0.09403 | \n", "0.01929 | \n", "19.085 | \n", "1 | \n", "0.458359 | \n", "0.819521 | \n", "-4.075192 | \n", "0.335590 | \n", "2.486855 | \n", "0.368674 | \n", "
| 2 | \n", "phon_R01_S01_3 | \n", "116.682 | \n", "131.111 | \n", "111.555 | \n", "0.01050 | \n", "0.00009 | \n", "0.00544 | \n", "0.00781 | \n", "0.01633 | \n", "0.05233 | \n", "... | \n", "0.08270 | \n", "0.01309 | \n", "20.651 | \n", "1 | \n", "0.429895 | \n", "0.825288 | \n", "-4.443179 | \n", "0.311173 | \n", "2.342259 | \n", "0.332634 | \n", "
| 3 | \n", "phon_R01_S01_4 | \n", "116.676 | \n", "137.871 | \n", "111.366 | \n", "0.00997 | \n", "0.00009 | \n", "0.00502 | \n", "0.00698 | \n", "0.01505 | \n", "0.05492 | \n", "... | \n", "0.08771 | \n", "0.01353 | \n", "20.644 | \n", "1 | \n", "0.434969 | \n", "0.819235 | \n", "-4.117501 | \n", "0.334147 | \n", "2.405554 | \n", "0.368975 | \n", "
| 4 | \n", "phon_R01_S01_5 | \n", "116.014 | \n", "141.781 | \n", "110.655 | \n", "0.01284 | \n", "0.00011 | \n", "0.00655 | \n", "0.00908 | \n", "0.01966 | \n", "0.06425 | \n", "... | \n", "0.10470 | \n", "0.01767 | \n", "19.649 | \n", "1 | \n", "0.417356 | \n", "0.823484 | \n", "-3.747787 | \n", "0.234513 | \n", "2.332180 | \n", "0.410335 | \n", "
5 rows × 24 columns
\n", "| \n", " | Model | \n", "Accuracy | \n", "Train_acc | \n", "
|---|---|---|---|
| 0 | \n", "LGBMClassifier | \n", "1.000000 | \n", "1.000000 | \n", "
| 3 | \n", "RandomForestClassifier | \n", "1.000000 | \n", "0.962025 | \n", "
| 5 | \n", "XGBClassifier | \n", "1.000000 | \n", "1.000000 | \n", "
| 7 | \n", "NeuralNet | \n", "1.000000 | \n", "1.000000 | \n", "
| 2 | \n", "DecisionTreeClassifier | \n", "0.972973 | \n", "0.936709 | \n", "
| 4 | \n", "GradientBoostingClassifier | \n", "0.972973 | \n", "1.000000 | \n", "
| 1 | \n", "KNeighborsClassifier | \n", "0.891892 | \n", "0.936709 | \n", "
| 6 | \n", "SupportVectorClassifier | \n", "0.891892 | \n", "0.898734 | \n", "
| Training Dataset size | \n", "(158, 22) | \n", "
| Validation Dataset size | \n", "None | \n", "
| CV | \n", "5 | \n", "
| Target variable | \n", "status | \n", "
| Optimization Metric | \n", "roc_auc | \n", "
| Initial number of Features | \n", "22 | \n", "
| Selected number of Features | \n", "13 | \n", "
| Selected Features | \n", "Index(['MDVPFoHz', 'MDVPFhiHz', 'MDVPFloHz', 'MDVPRAP', 'JitterDDP',\n", " 'ShimmerAPQ5', 'HNR', 'RPDE', 'DFA', 'spread1', 'spread2', 'D2', 'PPE'],\n", " dtype='object') | \n", "
| Selected Algorithm | \n", "ExtraTreesClassifier | \n", "
| End-to-end Elapsed Time (seconds) | \n", "77.8879 | \n", "
| Selected Hyperparameters | \n", "{'bootstrap': False, 'ccp_alpha': 0.0, 'class_weight': 'balanced', 'criterion': 'gini', 'max_depth': None, 'max_features': 0.1460769087812032, 'max_leaf_nodes': None, 'max_samples': None, 'min_impurity_decrease': 0.0, 'min_samples_leaf': 0.000625, 'min_samples_split': 0.00125, 'min_weight_fraction_leaf': 0.0, 'n_estimators': 100, 'n_jobs': 1, 'oob_score': False, 'random_state': 0, 'verbose': 0, 'warm_start': False} | \n", "
| Mean Validation Score | \n", "0.992 | \n", "
| AutoML n_jobs | \n", "4 | \n", "
| AutoML version | \n", "1.0 | \n", "
| Python version | \n", "3.7.12 | packaged by conda-forge | (default, Oct 26 2021, 06:08:53) \\n[GCC 9.4.0] | \n", "
| Rank based on Performance | \n", "Algorithm | \n", "#Samples | \n", "#Features | \n", "Mean Validation Score | \n", "Hyperparameters | \n", "CPU Time | \n", "Memory Usage | \n", "
|---|---|---|---|---|---|---|---|
| 2 | \n", "ExtraTreesClassifier_HT | \n", "158 | \n", "13 | \n", "0.9920 | \n", "{'class_weight': 'balanced', 'criterion': 'gini', 'max_features': 0.14608613955043395, 'min_samples_leaf': 0.000625, 'min_samples_split': 0.00125, 'n_estimators': 100} | \n", "1.9392 | \n", "0.0 | \n", "
| 3 | \n", "ExtraTreesClassifier_HT | \n", "158 | \n", "13 | \n", "0.9920 | \n", "{'class_weight': 'balanced_subsample', 'criterion': 'entropy', 'max_features': 0.1460769087812032, 'min_samples_leaf': 0.000625, 'min_samples_split': 0.00125, 'n_estimators': 100} | \n", "1.7138 | \n", "0.0 | \n", "
| 4 | \n", "ExtraTreesClassifier_HT | \n", "158 | \n", "13 | \n", "0.9920 | \n", "{'class_weight': 'balanced', 'criterion': 'entropy', 'max_features': 0.1460769087812032, 'min_samples_leaf': 0.000625, 'min_samples_split': 0.00125, 'n_estimators': 100} | \n", "2.0291 | \n", "0.0 | \n", "
| 5 | \n", "ExtraTreesClassifier_HT | \n", "158 | \n", "13 | \n", "0.9920 | \n", "{'class_weight': 'balanced_subsample', 'criterion': 'gini', 'max_features': 0.1460769087812032, 'min_samples_leaf': 0.000625, 'min_samples_split': 0.00125, 'n_estimators': 100} | \n", "1.9459 | \n", "0.0 | \n", "
| 6 | \n", "ExtraTreesClassifier_HT | \n", "158 | \n", "13 | \n", "0.9920 | \n", "{'class_weight': 'balanced', 'criterion': 'gini', 'max_features': 0.1460769087812032, 'min_samples_leaf': 0.000625, 'min_samples_split': 0.00125, 'n_estimators': 101} | \n", "1.7291 | \n", "0.0 | \n", "
| ... | \n", "... | \n", "... | \n", "... | \n", "... | \n", "... | \n", "... | \n", "... | \n", "
| 115 | \n", "DecisionTreeClassifier_AS | \n", "158 | \n", "22 | \n", "0.7684 | \n", "{'class_weight': None, 'max_features': 1.0, 'min_samples_leaf': 0.000625, 'min_samples_split': 0.00125} | \n", "0.1373 | \n", "0.0 | \n", "
| 116 | \n", "ExtraTreesClassifier_MIClassification_FS | \n", "158 | \n", "2 | \n", "0.7261 | \n", "{'n_estimators': 100, 'class_weight': 'balanced', 'criterion': 'gini', 'max_features': 0.777777778, 'min_samples_leaf': 0.000625, 'min_samples_split': 0.00125} | \n", "2.8954 | \n", "0.0 | \n", "
| 117 | \n", "ExtraTreesClassifier_HT | \n", "158 | \n", "13 | \n", "0.7219 | \n", "{'class_weight': None, 'criterion': 'gini', 'max_features': 0.07692307692307693, 'min_samples_leaf': 0.05627632998389018, 'min_samples_split': 0.012658227848101266, 'n_estimators': 5} | \n", "0.2005 | \n", "0.0 | \n", "
| 118 | \n", "ExtraTreesClassifier_HT | \n", "158 | \n", "13 | \n", "0.7219 | \n", "{'class_weight': None, 'criterion': 'gini', 'max_features': 0.07692307692307693, 'min_samples_leaf': 0.056281266692750936, 'min_samples_split': 0.012658227848101266, 'n_estimators': 5} | \n", "0.1709 | \n", "0.0 | \n", "
| 119 | \n", "ExtraTreesClassifier_ANOVAF_FS | \n", "158 | \n", "1 | \n", "0.5975 | \n", "{'n_estimators': 100, 'class_weight': 'balanced', 'criterion': 'gini', 'max_features': 0.777777778, 'min_samples_leaf': 0.000625, 'min_samples_split': 0.00125} | \n", "1.8457 | \n", "0.0 | \n", "
| Training Dataset size | \n", "(158, 22) | \n", "
| Validation Dataset size | \n", "None | \n", "
| CV | \n", "5 | \n", "
| Target variable | \n", "status | \n", "
| Optimization Metric | \n", "roc_auc | \n", "
| Initial number of Features | \n", "22 | \n", "
| Selected number of Features | \n", "22 | \n", "
| Selected Features | \n", "Index(['MDVPFoHz', 'MDVPFhiHz', 'MDVPFloHz', 'MDVPJitter', 'MDVPJitterAbs',\n", " 'MDVPRAP', 'MDVPPPQ', 'JitterDDP', 'MDVPShimmer', 'MDVPShimmerdB',\n", " 'ShimmerAPQ3', 'ShimmerAPQ5', 'MDVPAPQ', 'ShimmerDDA', 'NHR', 'HNR',\n", " 'RPDE', 'DFA', 'spread1', 'spread2', 'D2', 'PPE'],\n", " dtype='object') | \n", "
| Selected Algorithm | \n", "ExtraTreesClassifier | \n", "
| End-to-end Elapsed Time (seconds) | \n", "61.5294 | \n", "
| Selected Hyperparameters | \n", "{'bootstrap': False, 'ccp_alpha': 0.0, 'class_weight': 'balanced_subsample', 'criterion': 'gini', 'max_depth': None, 'max_features': 0.777777778, 'max_leaf_nodes': None, 'max_samples': None, 'min_impurity_decrease': 0.0, 'min_samples_leaf': 0.000625, 'min_samples_split': 0.00125, 'min_weight_fraction_leaf': 0.0, 'n_estimators': 100, 'n_jobs': 1, 'oob_score': False, 'random_state': 7, 'verbose': 0, 'warm_start': False} | \n", "
| Mean Validation Score | \n", "0.9759 | \n", "
| AutoML n_jobs | \n", "4 | \n", "
| AutoML version | \n", "1.0 | \n", "
| Python version | \n", "3.7.12 | packaged by conda-forge | (default, Oct 26 2021, 06:08:53) \\n[GCC 9.4.0] | \n", "
| Rank based on Performance | \n", "Algorithm | \n", "#Samples | \n", "#Features | \n", "Mean Validation Score | \n", "Hyperparameters | \n", "CPU Time | \n", "Memory Usage | \n", "
|---|---|---|---|---|---|---|---|
| 2 | \n", "ExtraTreesClassifier_ANOVAF_FS | \n", "158 | \n", "22 | \n", "0.9786 | \n", "{'n_estimators': 100, 'class_weight': 'balanced', 'criterion': 'gini', 'max_features': 0.777777778, 'min_samples_leaf': 0.000625, 'min_samples_split': 0.00125} | \n", "2.1906 | \n", "0.0 | \n", "
| 3 | \n", "ExtraTreesClassifier_AVGRanking_FS | \n", "158 | \n", "19 | \n", "0.9780 | \n", "{'n_estimators': 100, 'class_weight': 'balanced', 'criterion': 'gini', 'max_features': 0.777777778, 'min_samples_leaf': 0.000625, 'min_samples_split': 0.00125} | \n", "2.4699 | \n", "0.0 | \n", "
| 4 | \n", "ExtraTreesClassifier_ANOVAF_FS | \n", "158 | \n", "19 | \n", "0.9779 | \n", "{'n_estimators': 100, 'class_weight': 'balanced', 'criterion': 'gini', 'max_features': 0.777777778, 'min_samples_leaf': 0.000625, 'min_samples_split': 0.00125} | \n", "2.3972 | \n", "0.0 | \n", "
| 5 | \n", "ExtraTreesClassifier_RandomForestClassifier_FS | \n", "158 | \n", "16 | \n", "0.9776 | \n", "{'n_estimators': 100, 'class_weight': 'balanced', 'criterion': 'gini', 'max_features': 0.777777778, 'min_samples_leaf': 0.000625, 'min_samples_split': 0.00125} | \n", "2.0201 | \n", "0.0 | \n", "
| 6 | \n", "ExtraTreesClassifier_RandomForestClassifier_FS | \n", "158 | \n", "19 | \n", "0.9771 | \n", "{'n_estimators': 100, 'class_weight': 'balanced', 'criterion': 'gini', 'max_features': 0.777777778, 'min_samples_leaf': 0.000625, 'min_samples_split': 0.00125} | \n", "1.9625 | \n", "0.0 | \n", "
| ... | \n", "... | \n", "... | \n", "... | \n", "... | \n", "... | \n", "... | \n", "... | \n", "
| 93 | \n", "ExtraTreesClassifier_HT | \n", "158 | \n", "22 | \n", "0.7807 | \n", "{'class_weight': None, 'criterion': 'entropy', 'max_features': 0.045454545454545456, 'min_samples_leaf': 0.01888007212783866, 'min_samples_split': 0.012658227848101266, 'n_estimators': 5} | \n", "0.2444 | \n", "0.0 | \n", "
| 94 | \n", "ExtraTreesClassifier_HT | \n", "158 | \n", "22 | \n", "0.7807 | \n", "{'class_weight': None, 'criterion': 'entropy', 'max_features': 0.045454545454545456, 'min_samples_leaf': 0.01888500883669942, 'min_samples_split': 0.012658227848101266, 'n_estimators': 5} | \n", "0.2343 | \n", "0.0 | \n", "
| 95 | \n", "ExtraTreesClassifier_HT | \n", "158 | \n", "22 | \n", "0.7325 | \n", "{'class_weight': None, 'criterion': 'entropy', 'max_features': 0.045454545454545456, 'min_samples_leaf': 0.05627632998389018, 'min_samples_split': 0.012658227848101266, 'n_estimators': 5} | \n", "0.2098 | \n", "0.0 | \n", "
| 96 | \n", "ExtraTreesClassifier_HT | \n", "158 | \n", "22 | \n", "0.7325 | \n", "{'class_weight': None, 'criterion': 'entropy', 'max_features': 0.045454545454545456, 'min_samples_leaf': 0.056281266692750936, 'min_samples_split': 0.012658227848101266, 'n_estimators': 5} | \n", "0.1862 | \n", "0.0 | \n", "
| 97 | \n", "ExtraTreesClassifier_ANOVAF_FS | \n", "158 | \n", "1 | \n", "0.6017 | \n", "{'n_estimators': 100, 'class_weight': 'balanced', 'criterion': 'gini', 'max_features': 0.777777778, 'min_samples_leaf': 0.000625, 'min_samples_split': 0.00125} | \n", "2.2160 | \n", "0.0 | \n", "
| Feature | Value |
|---|---|
| DFA | 0.644692 |
| spread1 | -5.44004 |
| PPE | 0.218164 |
| MDVPFhiHz | 349.259 |
| MDVPJitterAbs | 4e-05 |
| ShimmerDDA | 0.02908 |
| MDVPFoHz | 144.188 |
| ShimmerAPQ5 | 0.012 |
| spread2 | 0.239764 |
| HNR | 22.333 |
| MDVPJitter | 0.00544 |
| MDVPShimmerdB | 0.192 |
| NHR | 0.01859 |
| MDVPAPQ | 0.02074 |
| JitterDDP | 0.00632 |
| MDVPShimmer | 0.02047 |
| ShimmerAPQ3 | 0.00969 |
| MDVPPPQ | 0.00292 |
| RPDE | 0.56738 |
| MDVPFloHz | 82.764 |
| D2 | 2.264501 |
| MDVPRAP | 0.00211 |
| Sample Space | \n", " \n", "root_mean_squared_error | \n", " \n", "pearson Analysis | \n", "
|---|---|---|
| Nt | \n", " \n", "0.121 | \n", " \n", "Corr=0.208 p=4.8260e-50 | \n",
"
| Nv_2 | \n", " \n", "0.039 | \n", " \n", "No score ----------- Black-box model predictions const. Surrogate model predictions const. | \n",
"
| Nv_4 | \n", " \n", "0.165 | \n", " \n", "Corr=0.178 p=0.012 | \n",
"
| Nv_16 | \n", " \n", "0.160 | \n", " \n", "Corr=0.144 p=0.042 | \n",
"
Performance
| \n", " | \n", " | \n", " | Actions Needed | \n", "
|---|---|---|---|
| Step | \n", "Status | \n", "Details | \n", "\n", " |
| initiate | \n", "Done | \n", "Initiated the model | \n", "\n", " |
| prepare() | \n", "Available | \n", "Generated runtime.yaml | \n", "\n", " |
| Generated score.py | \n", "\n", " | ||
| Serialized model | \n", "\n", " | ||
| Populated metadata(Custom, Taxonomy and Provenance) | \n", "\n", " | ||
| verify() | \n", "Not Available | \n", "Local tested .predict from score.py | \n", "\n", " |
| save() | \n", "Not Available | \n", "Conducted Introspect Test | \n", "\n", " |
| Uploaded artifact to model catalog | \n", "\n", " | ||
| deploy() | \n", "Not Available | \n", "Deployed the model | \n", "\n", " |
| predict() | \n", "Not Available | \n", "Called deployment predict endpoint | \n", "\n", " |
| \n", " | \n", " | \n", " | Actions Needed | \n", "
|---|---|---|---|
| Step | \n", "Status | \n", "Details | \n", "\n", " |
| initiate | \n", "Done | \n", "Initiated the model | \n", "\n", " |
| prepare() | \n", "Done | \n", "Generated runtime.yaml | \n", "\n", " |
| Generated score.py | \n", "\n", " | ||
| Serialized model | \n", "\n", " | ||
| Populated metadata(Custom, Taxonomy and Provenance) | \n", "\n", " | ||
| verify() | \n", "Available | \n", "Local tested .predict from score.py | \n", "\n", " |
| save() | \n", "Available | \n", "Conducted Introspect Test | \n", "\n", " |
| Uploaded artifact to model catalog | \n", "\n", " | ||
| deploy() | \n", "Not Available | \n", "Deployed the model | \n", "\n", " |
| predict() | \n", "Not Available | \n", "Called deployment predict endpoint | \n", "\n", " |
| \n", " | name | \n", "MDVPFoHz | \n", "MDVPFhiHz | \n", "MDVPFloHz | \n", "MDVPJitter | \n", "MDVPJitterAbs | \n", "MDVPRAP | \n", "MDVPPPQ | \n", "JitterDDP | \n", "MDVPShimmer | \n", "... | \n", "ShimmerDDA | \n", "NHR | \n", "HNR | \n", "status | \n", "RPDE | \n", "DFA | \n", "spread1 | \n", "spread2 | \n", "D2 | \n", "PPE | \n", "
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 25 | \n", "phon_R01_S06 | \n", "104.400 | \n", "206.002 | \n", "77.968 | \n", "0.00633 | \n", "0.000060 | \n", "0.00316 | \n", "0.00375 | \n", "0.00948 | \n", "0.03767 | \n", "... | \n", "0.05197 | \n", "0.02887 | \n", "22.066 | \n", "1 | \n", "0.522746 | \n", "0.737948 | \n", "-5.571843 | \n", "0.236853 | \n", "2.846369 | \n", "0.219514 | \n", "
| 26 | \n", "phon_R01_S06 | \n", "171.041 | \n", "208.313 | \n", "75.501 | \n", "0.00455 | \n", "0.000030 | \n", "0.00250 | \n", "0.00234 | \n", "0.00750 | \n", "0.01966 | \n", "... | \n", "0.02666 | \n", "0.01095 | \n", "25.908 | \n", "1 | \n", "0.418622 | \n", "0.720916 | \n", "-6.183590 | \n", "0.226278 | \n", "2.589702 | \n", "0.147403 | \n", "
| 27 | \n", "phon_R01_S06 | \n", "146.845 | \n", "208.701 | \n", "81.737 | \n", "0.00496 | \n", "0.000030 | \n", "0.00250 | \n", "0.00275 | \n", "0.00749 | \n", "0.01919 | \n", "... | \n", "0.02650 | \n", "0.01328 | \n", "25.119 | \n", "1 | \n", "0.358773 | \n", "0.726652 | \n", "-6.271690 | \n", "0.196102 | \n", "2.314209 | \n", "0.162999 | \n", "
| 28 | \n", "phon_R01_S06 | \n", "155.358 | \n", "227.383 | \n", "80.055 | \n", "0.00310 | \n", "0.000020 | \n", "0.00159 | \n", "0.00176 | \n", "0.00476 | \n", "0.01718 | \n", "... | \n", "0.02307 | \n", "0.00677 | \n", "25.970 | \n", "1 | \n", "0.470478 | \n", "0.676258 | \n", "-7.120925 | \n", "0.279789 | \n", "2.241742 | \n", "0.108514 | \n", "
| 29 | \n", "phon_R01_S06 | \n", "162.568 | \n", "198.346 | \n", "77.630 | \n", "0.00502 | \n", "0.000030 | \n", "0.00280 | \n", "0.00253 | \n", "0.00841 | \n", "0.01791 | \n", "... | \n", "0.02380 | \n", "0.01170 | \n", "25.678 | \n", "1 | \n", "0.427785 | \n", "0.723797 | \n", "-6.635729 | \n", "0.209866 | \n", "1.957961 | \n", "0.135242 | \n", "
| 30 | \n", "phon_R01_S07 | \n", "197.076 | \n", "206.896 | \n", "192.055 | \n", "0.00289 | \n", "0.000010 | \n", "0.00166 | \n", "0.00168 | \n", "0.00498 | \n", "0.01098 | \n", "... | \n", "0.01689 | \n", "0.00339 | \n", "26.775 | \n", "0 | \n", "0.422229 | \n", "0.741367 | \n", "-7.348300 | \n", "0.177551 | \n", "1.743867 | \n", "0.085569 | \n", "
| 31 | \n", "phon_R01_S07 | \n", "199.228 | \n", "209.512 | \n", "192.091 | \n", "0.00241 | \n", "0.000010 | \n", "0.00134 | \n", "0.00138 | \n", "0.00402 | \n", "0.01015 | \n", "... | \n", "0.01513 | \n", "0.00167 | \n", "30.940 | \n", "0 | \n", "0.432439 | \n", "0.742055 | \n", "-7.682587 | \n", "0.173319 | \n", "2.103106 | \n", "0.068501 | \n", "
| 32 | \n", "phon_R01_S07 | \n", "198.383 | \n", "215.203 | \n", "193.104 | \n", "0.00212 | \n", "0.000010 | \n", "0.00113 | \n", "0.00135 | \n", "0.00339 | \n", "0.01263 | \n", "... | \n", "0.01919 | \n", "0.00119 | \n", "30.775 | \n", "0 | \n", "0.465946 | \n", "0.738703 | \n", "-7.067931 | \n", "0.175181 | \n", "1.512275 | \n", "0.096320 | \n", "
| 33 | \n", "phon_R01_S07 | \n", "202.266 | \n", "211.604 | \n", "197.079 | \n", "0.00180 | \n", "0.000009 | \n", "0.00093 | \n", "0.00107 | \n", "0.00278 | \n", "0.00954 | \n", "... | \n", "0.01407 | \n", "0.00072 | \n", "32.684 | \n", "0 | \n", "0.368535 | \n", "0.742133 | \n", "-7.695734 | \n", "0.178540 | \n", "1.544609 | \n", "0.056141 | \n", "
| 34 | \n", "phon_R01_S07 | \n", "203.184 | \n", "211.526 | \n", "196.160 | \n", "0.00178 | \n", "0.000009 | \n", "0.00094 | \n", "0.00106 | \n", "0.00283 | \n", "0.00958 | \n", "... | \n", "0.01403 | \n", "0.00065 | \n", "33.047 | \n", "0 | \n", "0.340068 | \n", "0.741899 | \n", "-7.964984 | \n", "0.163519 | \n", "1.423287 | \n", "0.044539 | \n", "
10 rows × 24 columns
\n", "| \n", " | \n", " | \n", " | Actions Needed | \n", "
|---|---|---|---|
| Step | \n", "Status | \n", "Details | \n", "\n", " |
| initiate | \n", "Done | \n", "Initiated the model | \n", "\n", " |
| prepare() | \n", "Done | \n", "Generated runtime.yaml | \n", "\n", " |
| Generated score.py | \n", "\n", " | ||
| Serialized model | \n", "\n", " | ||
| Populated metadata(Custom, Taxonomy and Provenance) | \n", "\n", " | ||
| verify() | \n", "Done | \n", "Local tested .predict from score.py | \n", "\n", " |
| save() | \n", "Available | \n", "Conducted Introspect Test | \n", "\n", " |
| Uploaded artifact to model catalog | \n", "\n", " | ||
| deploy() | \n", "Not Available | \n", "Deployed the model | \n", "\n", " |
| predict() | \n", "Not Available | \n", "Called deployment predict endpoint | \n", "\n", " |
| \n", " | \n", " | \n", " | Actions Needed | \n", "
|---|---|---|---|
| Step | \n", "Status | \n", "Details | \n", "\n", " |
| initiate | \n", "Done | \n", "Initiated the model | \n", "\n", " |
| prepare() | \n", "Done | \n", "Generated runtime.yaml | \n", "\n", " |
| Generated score.py | \n", "\n", " | ||
| Serialized model | \n", "\n", " | ||
| Populated metadata(Custom, Taxonomy and Provenance) | \n", "\n", " | ||
| verify() | \n", "Done | \n", "Local tested .predict from score.py | \n", "\n", " |
| save() | \n", "Done | \n", "Conducted Introspect Test | \n", "\n", " |
| Uploaded artifact to model catalog | \n", "\n", " | ||
| deploy() | \n", "ACTIVE | \n", "Deployed the model | \n", "\n", " |
| predict() | \n", "Available | \n", "Called deployment predict endpoint | \n", "\n", " |
| \n", " | name | \n", "MDVPFoHz | \n", "MDVPFhiHz | \n", "MDVPFloHz | \n", "MDVPJitter | \n", "MDVPJitterAbs | \n", "MDVPRAP | \n", "MDVPPPQ | \n", "JitterDDP | \n", "MDVPShimmer | \n", "... | \n", "ShimmerDDA | \n", "NHR | \n", "HNR | \n", "status | \n", "RPDE | \n", "DFA | \n", "spread1 | \n", "spread2 | \n", "D2 | \n", "PPE | \n", "
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | \n", "phon_R01_S01 | \n", "119.992 | \n", "157.302 | \n", "74.997 | \n", "0.00784 | \n", "0.00007 | \n", "0.00370 | \n", "0.00554 | \n", "0.01109 | \n", "0.04374 | \n", "... | \n", "0.06545 | \n", "0.02211 | \n", "21.033 | \n", "1 | \n", "0.414783 | \n", "0.815285 | \n", "-4.813031 | \n", "0.266482 | \n", "2.301442 | \n", "0.284654 | \n", "
| 1 | \n", "phon_R01_S01 | \n", "122.400 | \n", "148.650 | \n", "113.819 | \n", "0.00968 | \n", "0.00008 | \n", "0.00465 | \n", "0.00696 | \n", "0.01394 | \n", "0.06134 | \n", "... | \n", "0.09403 | \n", "0.01929 | \n", "19.085 | \n", "1 | \n", "0.458359 | \n", "0.819521 | \n", "-4.075192 | \n", "0.335590 | \n", "2.486855 | \n", "0.368674 | \n", "
| 2 | \n", "phon_R01_S01 | \n", "116.682 | \n", "131.111 | \n", "111.555 | \n", "0.01050 | \n", "0.00009 | \n", "0.00544 | \n", "0.00781 | \n", "0.01633 | \n", "0.05233 | \n", "... | \n", "0.08270 | \n", "0.01309 | \n", "20.651 | \n", "1 | \n", "0.429895 | \n", "0.825288 | \n", "-4.443179 | \n", "0.311173 | \n", "2.342259 | \n", "0.332634 | \n", "
| 3 | \n", "phon_R01_S01 | \n", "116.676 | \n", "137.871 | \n", "111.366 | \n", "0.00997 | \n", "0.00009 | \n", "0.00502 | \n", "0.00698 | \n", "0.01505 | \n", "0.05492 | \n", "... | \n", "0.08771 | \n", "0.01353 | \n", "20.644 | \n", "1 | \n", "0.434969 | \n", "0.819235 | \n", "-4.117501 | \n", "0.334147 | \n", "2.405554 | \n", "0.368975 | \n", "
| 4 | \n", "phon_R01_S01 | \n", "116.014 | \n", "141.781 | \n", "110.655 | \n", "0.01284 | \n", "0.00011 | \n", "0.00655 | \n", "0.00908 | \n", "0.01966 | \n", "0.06425 | \n", "... | \n", "0.10470 | \n", "0.01767 | \n", "19.649 | \n", "1 | \n", "0.417356 | \n", "0.823484 | \n", "-3.747787 | \n", "0.234513 | \n", "2.332180 | \n", "0.410335 | \n", "
| ... | \n", "... | \n", "... | \n", "... | \n", "... | \n", "... | \n", "... | \n", "... | \n", "... | \n", "... | \n", "... | \n", "... | \n", "... | \n", "... | \n", "... | \n", "... | \n", "... | \n", "... | \n", "... | \n", "... | \n", "... | \n", "... | \n", "
| 190 | \n", "phon_R01_S50 | \n", "174.188 | \n", "230.978 | \n", "94.261 | \n", "0.00459 | \n", "0.00003 | \n", "0.00263 | \n", "0.00259 | \n", "0.00790 | \n", "0.04087 | \n", "... | \n", "0.07008 | \n", "0.02764 | \n", "19.517 | \n", "0 | \n", "0.448439 | \n", "0.657899 | \n", "-6.538586 | \n", "0.121952 | \n", "2.657476 | \n", "0.133050 | \n", "
| 191 | \n", "phon_R01_S50 | \n", "209.516 | \n", "253.017 | \n", "89.488 | \n", "0.00564 | \n", "0.00003 | \n", "0.00331 | \n", "0.00292 | \n", "0.00994 | \n", "0.02751 | \n", "... | \n", "0.04812 | \n", "0.01810 | \n", "19.147 | \n", "0 | \n", "0.431674 | \n", "0.683244 | \n", "-6.195325 | \n", "0.129303 | \n", "2.784312 | \n", "0.168895 | \n", "
| 192 | \n", "phon_R01_S50 | \n", "174.688 | \n", "240.005 | \n", "74.287 | \n", "0.01360 | \n", "0.00008 | \n", "0.00624 | \n", "0.00564 | \n", "0.01873 | \n", "0.02308 | \n", "... | \n", "0.03804 | \n", "0.10715 | \n", "17.883 | \n", "0 | \n", "0.407567 | \n", "0.655683 | \n", "-6.787197 | \n", "0.158453 | \n", "2.679772 | \n", "0.131728 | \n", "
| 193 | \n", "phon_R01_S50 | \n", "198.764 | \n", "396.961 | \n", "74.904 | \n", "0.00740 | \n", "0.00004 | \n", "0.00370 | \n", "0.00390 | \n", "0.01109 | \n", "0.02296 | \n", "... | \n", "0.03794 | \n", "0.07223 | \n", "19.020 | \n", "0 | \n", "0.451221 | \n", "0.643956 | \n", "-6.744577 | \n", "0.207454 | \n", "2.138608 | \n", "0.123306 | \n", "
| 194 | \n", "phon_R01_S50 | \n", "214.289 | \n", "260.277 | \n", "77.973 | \n", "0.00567 | \n", "0.00003 | \n", "0.00295 | \n", "0.00317 | \n", "0.00885 | \n", "0.01884 | \n", "... | \n", "0.03078 | \n", "0.04398 | \n", "21.209 | \n", "0 | \n", "0.462803 | \n", "0.664357 | \n", "-5.724056 | \n", "0.190667 | \n", "2.555477 | \n", "0.148569 | \n", "
195 rows × 24 columns
\n", "| \n", " | \n", " | \n", " | Actions Needed | \n", "
|---|---|---|---|
| Step | \n", "Status | \n", "Details | \n", "\n", " |
| initiate | \n", "Done | \n", "Initiated the model | \n", "\n", " |
| prepare() | \n", "Done | \n", "Generated runtime.yaml | \n", "\n", " |
| Generated score.py | \n", "\n", " | ||
| Serialized model | \n", "\n", " | ||
| Populated metadata(Custom, Taxonomy and Provenance) | \n", "\n", " | ||
| verify() | \n", "Done | \n", "Local tested .predict from score.py | \n", "\n", " |
| save() | \n", "Done | \n", "Conducted Introspect Test | \n", "\n", " |
| Uploaded artifact to model catalog | \n", "\n", " | ||
| deploy() | \n", "DELETED | \n", "Deployed the model | \n", "\n", " |
| predict() | \n", "Not Available | \n", "Called deployment predict endpoint | \n", "\n", " |