Iter fold

[Sauro98]

This PR introduces the iter_fold method for k_folding. The main points are:

Linfa/src

• Modified Fit trait to remove training set lifetime
• Implemented iter_folding without cloning

Linfa-kernel

• Introduced new trait Inner to represent an inner matrix. Implementors of this trait are: Array2, ArrayView2, CsMat, CsMatView
• enum KernelInner now takes two Inner as parameters, one for the dense implementation and one for the sparse implementation
• Renamed Kernel to KernelBase, which now takes the two Inner types for the KernelInner enum
• Added type Kernel<'a, F> which is a kernel that keeps the data in an ArrayView2 and has an owned inner matrix (the most common case)
• Added type KernelOwned<F> for which the data is owned too
• Added type KernelView<'a, F> which has a view on both its data and inner matrix
• Implemented functions view() and to_owned() to switch between the various types

This was done to be able to have both a kernel that borrows data with a lifetime and one that owns it with just one struct

Linfa-svm

• Modified implementation so that now Svm owns the kernel data (via a KernelOwned attribute)
• Adjusted to new Fit definition and kernel types
• Added tests for iter_fold both for regression and classification to show that it works

Other sub crates

• Adjuster for new Fit definition and kernel types

This doesn't address the points on #70 about the Dynamic Kernel type and Svm that only keeps its support vectors because I wanted to have a solid and approved basis before doing any additional work.

[codecov-io]

Codecov Report

Merging #77 (a58943f) into master (923b82f) will decrease coverage by 0.46%.
The diff coverage is 38.51%.

@@            Coverage Diff             @@
##           master      #77      +/-   ##
==========================================
- Coverage   54.49%   54.02%   -0.47%     
==========================================
  Files          62       63       +1     
  Lines        4318     4583     +265     
==========================================
+ Hits         2353     2476     +123     
- Misses       1965     2107     +142     

Impacted Files	Coverage Δ
linfa-elasticnet/src/algorithm.rs	82.63% <ø> (ø)
linfa-linear/src/ols.rs	67.96% <ø> (ø)
linfa-reduction/src/diffusion_map/algorithms.rs	0.00% <0.00%> (ø)
linfa-kernel/src/inner.rs	19.11% <19.11%> (ø)
src/dataset/impl_dataset.rs	36.02% <26.31%> (-1.82%)	⬇️
linfa-svm/src/regression.rs	45.71% <26.66%> (+1.11%)	⬆️
linfa-svm/src/classification.rs	51.98% <28.00%> (-10.44%)	⬇️
linfa-svm/src/solver_smo.rs	36.29% <30.58%> (+0.98%)	⬆️
linfa-svm/src/permutable_kernel.rs	46.34% <31.57%> (-10.81%)	⬇️
linfa-kernel/src/lib.rs	71.78% <38.46%> (-1.97%)	⬇️
... and 17 more

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[bytesnake]

thanks! I will look into this in the next days :)

[bytesnake]

okay I added some comments on the PR. This is really awesome work 👍
I think it would be better to separate Kernel from Dataset in order to resolve the ambiguities between Kernel and OwnedKernel. I added some comments how this can be realized.

After merging this, I will investigate how to simplify the API with Borrow

[bytesnake]

you still have to remove the commented parameters, but for my part we can merge this

[Sauro98]

my bad, I forgot to remove them 👍🏻