Last week we wrote about multidimensional linear models. We discussed a case in which a k-dimensional vector of the dependent variables is related to a grouping variable. We look at matrices E and H in order to find out whether there is any relationship (see the previous blog).
https://deepsense.ai/wp-content/uploads/2019/02/Canonical-discriminant-analyses-and-HE-plots.jpg3371140Przemyslaw Biecekhttps://deepsense.ai/wp-content/uploads/2019/04/DS_logo_color.svgPrzemyslaw Biecek2015-02-26 06:30:552019-07-09 10:04:32Canonical discriminant analyses and HE plots
GPS helps the drivers to avoid traffic jams, yet in more advanced uses it allows for fleet management or remote drone strikes. It is just the same with visualization. Bars and dots can be used to present a set of several means but there are also more advanced uses…
Spark wins more and more hearts. And no wonder, comments from different sources tell us about a significant speed up (by an order of magnitude) for analysis of big datasets. Well-developed system for caching objects in memory allows us to avoid torturing hard discs during iterative operations performed on same data.
Do you know where Kamil Stoch earns most of his points in season 2013/2014? Some time ago I came across a pheatmaps package for R software which generates much nicer heat maps than the standard heatmap() function. This is why the package is named…
A friend of mine took part in a project in which he had to perform future prediction of Y characteristic. The problem was that Y characteristic showed an increasing trend over time. For the purposes of this post let us assume that Y characteristic was energy demand or milk yield of cows or any other characteristic that with positive trend over time.
https://deepsense.ai/wp-content/uploads/2019/02/Is-a-simple-linear-regression-able-to-knock-spots-off-SVM-and-Random-Forest.jpg3371140Przemyslaw Biecekhttps://deepsense.ai/wp-content/uploads/2019/04/DS_logo_color.svgPrzemyslaw Biecek2015-01-15 06:30:142019-07-09 08:28:08Is a simple linear regression able to knock spots off SVM and Random Forest?
Canonical discriminant analyses and HE plots
/in Blog posts, Data science /by Przemyslaw BiecekLast week we wrote about multidimensional linear models. We discussed a case in which a k-dimensional vector of the dependent variables is related to a grouping variable. We look at matrices E and H in order to find out whether there is any relationship (see the previous blog).
HE plots
/in Blog posts, Data science /by Przemyslaw BiecekGPS helps the drivers to avoid traffic jams, yet in more advanced uses it allows for fleet management or remote drone strikes. It is just the same with visualization. Bars and dots can be used to present a set of several means but there are also more advanced uses…
Spark + R = SparkR
/in Blog posts, Data science /by Przemyslaw BiecekSpark wins more and more hearts. And no wonder, comments from different sources tell us about a significant speed up (by an order of magnitude) for analysis of big datasets. Well-developed system for caching objects in memory allows us to avoid torturing hard discs during iterative operations performed on same data.
Pretty heat maps
/in Blog posts, Data science /by Przemyslaw BiecekDo you know where Kamil Stoch earns most of his points in season 2013/2014? Some time ago I came across a pheatmaps package for R software which generates much nicer heat maps than the standard heatmap() function. This is why the package is named…
Is a simple linear regression able to knock spots off SVM and Random Forest?
/in Blog posts, Data science /by Przemyslaw BiecekA friend of mine took part in a project in which he had to perform future prediction of Y characteristic. The problem was that Y characteristic showed an increasing trend over time. For the purposes of this post let us assume that Y characteristic was energy demand or milk yield of cows or any other characteristic that with positive trend over time.