Oracle Data Mining ODM

Oracle Data Mining ODM provides powerful data mining functionality and enables the users to discover new insights in hidden data. Oracle Data Mining ODM  has several data mining and data analysis algorithms and is part of  Oracle Relational Database Management System Enterprise Edition.

These algorithms provide means for creation, manipulation, application, test and deployment of models. They are used for classification, prediction, regression, associations, feature selection, anomaly detection, feature extraction, and specialized analytics.  The models are implemented in Oracle database kernel and are stored as database objects.

Models can be created using a graphical user interface. Business analysts can do predictive analytics using Oracle spreadsheet ad in for predictive analytics, a microsoft excel  adaptor.

Most of the well known machine learning approaches such as decision trees, naive bayes, support vector machines, generalized linear model for predictive mining, association rules, K-means and orthogonal partitioning, clustering, and non-negative matrix factorization are available. Text mining is also available in Oracle Data Mining ODM.

Oracle Data Mining

Oracle Data Mining (ODM) provides powerful data mining functionality as native SQL functions within the Oracle Database. Oracle Data Mining is implemented in the Oracle Database kernel, and mining models are first class database objects. Oracle Data Mining processes use built-in features of Oracle Database to maximize scalability and make efficient use of system resources.

Data mining within Oracle Database offers many advantages. With Oracle Data Mining, no data movement or conversion is needed. This makes the entire mining process less complex, time-consuming, and error-prone. Only users with the appropriate privileges can score (apply) mining models.

Oracle Data Mining

Oracle Data Mining can automatically manage key steps in the data preparation process. Additionally, Oracle Database provides extensive administrative tools for preparing and managing data. Oracle Data Mining can easily deliver mining results based on current data, thereby maximizing its timeliness and relevance. Oracle Data Mining can easily be integrated with other analytical features of the database, such as statistical analysis and OLAP.

Oracle Data Mining

Oracle Data Mining ODM

Functions of Oracle Data Mining ODM

• Data transformation and model analysis:  data sampling, binning, discretization and model exploration, evaluation and analysis.
• Feature selection attribute : Minimum description length .
• Classification: naive bayes , generalized linear model for logistic regression, support vector machine, decision trees,
• Anomaly detection : one-class Support Vector Machine
• Regression : support vector machine and generalized linear model for Multiple regression
• Clustering: enhanced k-means and orthogonal partitioning clustering.
• Association rule learning: itemsets and association rules.
• Feature extraction: non-negative matrix factorization .
• Text and spatial mining: combined text and non-text columns of input data and GIS data.

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