Usage.md

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+copied from prev page:
+- Install any packages you want to use. For our example, switch to the package manager with "\]" and run:
+
+   ```
+   add LowRankModels
+   add DecisionTree
+   ```
+- Congratulations! As an example, run:
+
+   ```
+   using ConML
+   using LowRankModels # some algorithms for Construction and Reconstruction, use what you want
+   using DecisionTree
+   
+   toy = open("Path\\To\\toy.csv", "r")
+   readline(toy) # skip header
+   
+   # empty arrays for the data
+   T = Vector{Int}()
+   Sigma = Vector{String}()
+   Z = Vector{String}()
+   data = Vector{Vector{Float64}}()
+   
+   # separate data from metadata columns
+   for rline in readlines(toy)
+       line = split(rline,',')
+       push!(T, parse(Int,line[353]))
+       push!(Sigma, string(line[354]))
+       push!(Z, string(line[355]))
+       push!(data, map(x -> parse(Float64,x),line[2:352]))
+   end
+   
+   # cast it into a proper format for the algorithm
+   block = ConML.VMS{Float64}(T, Sigma, Z, data)
+   
+   # set parameters
+   # we have to specify values for which no defaults exist
+   par = ConML.ParametersConML(LearnBlockMinimum = 1, maxCategories = 10, MinCategorySize = 20, maxFilterFeatures = 1000, maxFilterSamples = 2000)
+   # create empty knowledge base
+   kb = ConML.KnowledgeBase{Int}(ConML.VMS{Int}(),Vector{ConML.MachineModel}())
+   # create steps for the algorithm
+   myConstruction = ConML.Construct([LowRankModels.KMeans(k=2), LowRankModels.KMeans(k=3), LowRankModels.KMeans(k=4)])
+   myReconstruction = ConML.Reconstruct([DecisionTree.DecisionTreeClassifier(max_depth=2), DecisionTree.AdaBoostStumpClassifier(n_iterations=10)])
+   featureSelection = ConML.FeatureSelector()
+   
+   # make a pipeline
+   learn = ConML.LearnerConML(kb, par, [ConML.searchLearnBlocks, myConstruction, featureSelection, myReconstruction])
+   
+   # feed it!
+   learn(block)
+   
+   ```
+- To update the packages, navigate to the project folder and do a git pull. Afterwards, go to the julia package manager ("\]") and run "update".
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