[jira] [Updated] (IGNITE-9283) [ML] Add Discrete Cosine preprocessor
[ https://issues.apache.org/jira/browse/IGNITE-9283?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] Alexey Zinoviev updated IGNITE-9283: Labels: newbie (was: ) > [ML] Add Discrete Cosine preprocessor > - > > Key: IGNITE-9283 > URL: https://issues.apache.org/jira/browse/IGNITE-9283 > Project: Ignite > Issue Type: Sub-task > Components: ml >Affects Versions: 3.0 >Reporter: Alexey Zinoviev >Assignee: Ilya Lantukh >Priority: Major > Labels: newbie > Time Spent: 40m > Remaining Estimate: 0h > > Add [https://en.wikipedia.org/wiki/Discrete_cosine_transform] > Please look at the MinMaxScaler or Normalization packages in preprocessing > package. > Add classes if required > 1) Preprocessor > 2) Trainer > 3) custom PartitionData if shuffling is a step of algorithm > > Requirements for successful PR: > # PartitionedDataset usage > # Trainer-Model paradigm support > # Tests for Model and for Trainer (and other stuff) > # Example of usage with small, but famous dataset like IRIS, Titanic or > House Prices > # Javadocs/codestyle according guidelines > > -- This message was sent by Atlassian Jira (v8.3.4#803005)
[jira] [Updated] (IGNITE-9283) [ML] Add Discrete Cosine preprocessor
[ https://issues.apache.org/jira/browse/IGNITE-9283?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] Aleksey Zinoviev updated IGNITE-9283: - Affects Version/s: 3.0 > [ML] Add Discrete Cosine preprocessor > - > > Key: IGNITE-9283 > URL: https://issues.apache.org/jira/browse/IGNITE-9283 > Project: Ignite > Issue Type: Sub-task > Components: ml >Affects Versions: 3.0 >Reporter: Aleksey Zinoviev >Assignee: Ilya Lantukh >Priority: Major > Time Spent: 40m > Remaining Estimate: 0h > > Add [https://en.wikipedia.org/wiki/Discrete_cosine_transform] > Please look at the MinMaxScaler or Normalization packages in preprocessing > package. > Add classes if required > 1) Preprocessor > 2) Trainer > 3) custom PartitionData if shuffling is a step of algorithm > > Requirements for successful PR: > # PartitionedDataset usage > # Trainer-Model paradigm support > # Tests for Model and for Trainer (and other stuff) > # Example of usage with small, but famous dataset like IRIS, Titanic or > House Prices > # Javadocs/codestyle according guidelines > > -- This message was sent by Atlassian Jira (v8.3.4#803005)
[jira] [Updated] (IGNITE-9283) [ML] Add Discrete Cosine preprocessor
[ https://issues.apache.org/jira/browse/IGNITE-9283?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] Aleksey Zinoviev updated IGNITE-9283: - Description: Add [https://en.wikipedia.org/wiki/Discrete_cosine_transform] Please look at the MinMaxScaler or Normalization packages in preprocessing package. Add classes if required 1) Preprocessor 2) Trainer 3) custom PartitionData if shuffling is a step of algorithm Requirements for successful PR: # PartitionedDataset usage # Trainer-Model paradigm support # Tests for Model and for Trainer (and other stuff) # Example of usage with small, but famous dataset like IRIS, Titanic or House Prices # Javadocs/codestyle according guidelines was: Add [https://en.wikipedia.org/wiki/Discrete_cosine_transform] Please look at the MinMaxScaler or Normalization packages in preprocessing package. Add classes if required 1) Preprocessor 2) Trainer 3) custom PartitionData if shuffling is a step of algorithm > [ML] Add Discrete Cosine preprocessor > - > > Key: IGNITE-9283 > URL: https://issues.apache.org/jira/browse/IGNITE-9283 > Project: Ignite > Issue Type: Sub-task > Components: ml >Reporter: Aleksey Zinoviev >Priority: Major > > Add [https://en.wikipedia.org/wiki/Discrete_cosine_transform] > Please look at the MinMaxScaler or Normalization packages in preprocessing > package. > Add classes if required > 1) Preprocessor > 2) Trainer > 3) custom PartitionData if shuffling is a step of algorithm > > Requirements for successful PR: > # PartitionedDataset usage > # Trainer-Model paradigm support > # Tests for Model and for Trainer (and other stuff) > # Example of usage with small, but famous dataset like IRIS, Titanic or > House Prices > # Javadocs/codestyle according guidelines > > -- This message was sent by Atlassian JIRA (v7.6.3#76005)
[jira] [Updated] (IGNITE-9283) [ML] Add Discrete Cosine preprocessor
[ https://issues.apache.org/jira/browse/IGNITE-9283?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] Aleksey Zinoviev updated IGNITE-9283: - Component/s: ml > [ML] Add Discrete Cosine preprocessor > - > > Key: IGNITE-9283 > URL: https://issues.apache.org/jira/browse/IGNITE-9283 > Project: Ignite > Issue Type: Sub-task > Components: ml >Reporter: Aleksey Zinoviev >Priority: Major > > Add [https://en.wikipedia.org/wiki/Discrete_cosine_transform] > Please look at the MinMaxScaler or Normalization packages in preprocessing > package. > Add classes if required > 1) Preprocessor > 2) Trainer > 3) custom PartitionData if shuffling is a step of algorithm > > -- This message was sent by Atlassian JIRA (v7.6.3#76005)
