The samples lie on a manifold of much lower dimension (say around 200 for instance).
The PCA algorithm can be used to linearly transform the data while both reducing the dimensionality and preserve most of the explained variance at the same time.
In Hibernate, only the “relationship owner” should maintain the relationship, and the “inverse” keyword is created to defines which side is the owner to maintain the relationship. ) Hibernate: update mkyongdb.stock_daily_record set STOCK_ID=?
However the “inverse” keyword itself is not verbose enough, I would suggest change the keyword to “relationship_owner“.
En KF is related to the particle filter (in this context, a particle is the same thing as ensemble member) but the En KF makes the assumption that all probability distributions involved are Gaussian; when it is applicable, it is much more efficient than the particle filter.
Furthermore we know that the intrinsic dimensionality of the data is much lower than 4096 since all pictures of human faces look somewhat alike.
The original Kalman Filter assumes that all pdfs are Gaussian (the Gaussian assumption) and provides algebraic formulas for the change of the mean and the covariance matrix by the Bayesian update, as well as a formula for advancing the covariance matrix in time provided the system is linear.
However, maintaining the covariance matrix is not feasible computationally for high-dimensional systems. En KFs represent the distribution of the system state using a collection of state vectors, called an ensemble, and replace the covariance matrix by the sample covariance computed from the ensemble.
Always put inverse=”true” in your collection variable ? Now, it means “stock Daily Records” is the relationship owner, and “stock” will not maintains the relationship. When a “Stock” object is saved, Hibernate will generated two SQL insert statements.
There are many Hibernate articles try to explain the “inverse” with many Hibernate “official” jargon, which is very hard to understand (at least to me). ) Hibernate: update mkyongdb.stock_daily_record set STOCK_ID=? session.begin Transaction(); Stock stock = new Stock(); Stock Code("7052"); Stock Name("PADINI"); Stock Daily Record stock Daily Records = new Stock Daily Record(); stock Daily Price Open(new Float("1.2")); stock Daily Price Close(new Float("1.1")); stock Daily Price Change(new Float("10.0")); stock Daily Volume(3000000L); stock Daily Date(new Date()); stock Daily Stock(stock); Stock Daily Records().add(stock Daily Records); session.save(stock); session.save(stock Daily Records); Transaction().commit(); Hibernate: insert into mkyongdb.stock (STOCK_CODE, STOCK_NAME) values (? ) Hibernate: insert into mkyongdb.stock_daily_record (STOCK_ID, PRICE_OPEN, PRICE_CLOSE, PRICE_CHANGE, VOLUME, DATE) values (?
This is the most confusing keyword in Hibernate, at least i took quite a long time to understand it.