- Fixing bug: local clusters' centroid method crashes when text or categorical fields are not present in input data.
- Adding local cluster to produce centroid predictions locally.
- Adding shared urls to datasets.
- Fixing bug: error renaming variables.
- Adding the ability to change the remote server domain in the API connection constructor (for VPCs).
- Adding the ability to generate datasets from clusters.
- Fixing bug when using api.ok method for centroids and batch centroids.
- Docs and test updates.
- Adding REST methods to manage clusters, centroids and batch centroids.
- Adding the average_confidence method to local models.
- Fixing bug in pprint for predictions with input data keyed by field names.
- Changing Fields object constructor to accept also source, dataset or model resources.
- Changing error message when create_source calls result in http errors to standarize them.
- Simplifying create_prediction calls because now API accepts field names as input_data keys.
- Adding missing_counts and error_counts to report the missing values and error counts per field in the dataset.
- Adding error to regression local predictions using proportional missing strategy.
- Adding proportional missing strategy to MultiModel and solving tie breaks in remote predictions.
- Adding new output options to model's python, rules and tableau outputs: ability to extract the branch of the model leading to a certain node with or without the hanging subtree.
- Adding HTTP_TOO_MANY_REQUESTS error handling in REST API calls.
- Adding Tableau-ready ouput to local model code generators.
- Fixing getters: getter for batch predictions was missing.
- Improving BaseModel and Model. If they receive a partial model structure with a correct model id, the needed model resource is downloaded and stored (if storage is enabled in the given api connection).
- Improving local ensemble. Adding a new fields attribute that contains all the fields used in its models.
- Adding a summarize method to local ensembles with data distribution and field importance information.
- Fixes bug in regressions predictions with ensembles and plurality without confidence information. Predictions values were not normalized.
- Updating copyright information.
- Fixes bug in create calls: the user provided args dictionaries were updated inside the calls.
- Changing the source for ensemble field importance computations.
- Fixes bug in http_ok adding the valid state for updates.
- Adding more info to error messages in REST methods.
- Adding new missing fields strategy in predict method.
- Fixes bug in shared models: credentials where not properly set.
- Adding batch predictions REST methods.
- Fixes bug in local ensembles with more than 200 fields.
- Fixes bug in summarize method of local models: field importance report crashed.
- Fixes bug in status method of the BigML connection object: status for async uploads of source files crashed while uploading.
- Adding threshold combiner to MultiModel objects.
- Adding a function printing field importance to ensembles.
- Changing Model to add a lightweight BaseModel class with no Tree information.
- Adding function to get resource type from resource id or structure.
- Adding resource type checks to REST functions.
- Adding threshold as new combination method for local ensembles.
- Fixes duplication changing field names in local model if they are not unique.
- Adds the environment variables and adapts the create_prediction method to create predictions using a different prediction server.
- Support for shared models.
- Adds text analysis local predict function
- Modifies outputs for text analysis: rules, summary, python, hadoop
- Fixes temporarily problems in predictions for regression models and ensembles
- Adds en-gb to the list of available locales, avoiding spurious warnings
- Changes warning logger level to info
- Adds fields method to retrieve only preferred fields
- Fixes error message when no valid resource id is provided in check_resource
- Fixes check_resource method that was not using query-string data
- Add list of models as argument in Ensemble constructor
- MultiModel has BigML connection as a new optional argument
- Fixes Multimodel list_models method
- Fixes check_resource method for predictions
- Adds local configuration environment variable BIGML_DOMAIN replacing BIGML_URL and BIGML_DEV_URL
- Refactors Ensemble and Model's predict method
- Adds splits in datasets to generate new datasets
- Adds evaluations for ensembles
- REST API methods for model ensembles
- New method returning the leaves of tree models
- Improved error handling in GET methods
- Adds combined confidence to combined predictions
- Fixes get_status for resources that have no status info
- Fixes bug: public datasets, that should be downloadable, weren't
- Fixes bug: no status info in public models, now shows FINISHED status code
- Adds more file-like objects (e.g. stdin) support in create_source input
- Refactoring Fields pair method and Model predict method to increase
- Adds some more locale aliases
- Adds evaluation api functions
- New prediction combination method: probability weighted
- Refactors MultiModels lists of predictions into MultiVote
- Multimodels partial predictions: new format
- Improved locale management
- Adds new features to MultiModel to allow local batch predictions
- Improved combined predictions
- Adds local predictions options: plurality, confidence weighted
- Warning message to inform of locale default if verbose mode
- Fix locale code for windows
- Fix remote predictions for input data containing fields not included in rules
- Tiny fixes
- Fix local predictions for input data containing fields not included in rules
- Overall clean up
- A few tiny fixes
- Multi models to generate predictions from multiple local models
- Adds hadoop-python code generation to create local predictions
- Fix Python generation
- Add a debug flag to log https requests and responses
- Type conversion in fields pairing
- Fix missing distribution field in new models
- Add new Field class to deal with BigML auto-generated ids
- Add by_name flag to predict methods to avoid reverse name lookups
- Add summarize method in models to generate class grouped printed output
- Development Mode
- Remote Sources
- Bigger files streamed with Poster
- Asynchronous Uploading
- Local Models
- Local Predictions
- Rule Generation
- Python Generation
- Overall clean up
- Initial release for the "andromeda" version of BigML.io.