Difference between revisions of "Meteos/DatasetsandModels"
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[http://spark.apache.org/docs/1.6.0/mllib-collaborative-filtering.html#collaborative-filtering Recommendation Model] | [http://spark.apache.org/docs/1.6.0/mllib-collaborative-filtering.html#collaborative-filtering Recommendation Model] | ||
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| + | [http://spark.apache.org/docs/1.6.0/ml-features.html#word2vec Word2Vec Model] | ||
=== ML === | === ML === | ||
Not Supported. | Not Supported. | ||
Revision as of 04:48, 13 December 2016
Contents
Meteos Dataset
Dataset is a data to create a prediction model.
DataSet Format
Meteos currently supports following data format.
Supported dataset format differs depending on pediction models.
All of models support cvs dataset format, however libsvm dataset format is only supported by LinearRegression Model, LogisticRegression Model and DecisionTree Mode.
CSV data format
<label>,<value1>,<value2>, ... <valueN>
LibSVM data format
<label> <index1>:<value1> <index2>:<value2> ... <indexN>:<valueN>
Text data format is only supported Word2Vec Model. Any other Model can not handle text data.
Text data format
This is a text data format
DataSet URL
When creating a prediction model, user specify a "source_dataset_url" parameter which show the place where dataset is located.
A Source_dataset_url has two url types as follows:
Swift URL
Swift URL is used when creating a model from dataset in swift.
If it is no neccesary to parse a dataset, user can create a model from dataset in swift directly by specify source_data_url as below.
swift://<container_name>/<object_name>
Internal HDFS URL
Internal HDFS URL is used when creating a model from internal hdfs of meteos experiment.
"Internal" is meaning that dataset has been already downloaded or parsed by Meteos.
When creating a model from dataset in hdfs, user have to specify a url as below.
internal://<dataset_id>
Meteos Prediction Model
Currently Meteos supports these following prediction models of Apache Spark.
Apache Spark has two machine learning libraries (MLlib and Ml).
MLlib and ML has multiple prediction models by data mining and machine learning algorithms.
MLlib
ML
Not Supported.
