minor editing of ml reference chapters and utils (wording, typos, sty…

notebooks/noj_book/sklearn_reference.clj

@@ -12,21 +12,22 @@
    [noj-book.utils.render-tools-sklearn]
    [scicloj.sklearn-clj.ml]))
 
-;;## Sklearn model reference
+;; ## Sklearn model reference
 
-;;Below we find all sklearn models with their parameters and the original documentation.
+;; Below we find all [sklearn](https://scikit-learn.org/stable/) models with their parameters and the original documentation.
 ;;
-;;The parameters are given as Clojure keys in kebap-case. As the document texts are 
-;;imported from python they refer to the python spelling of the parameter. 
+;; The parameters are given as Clojure keys in kebab-case.
+;; As the document texts are imported from Python, they refer to the
+;; Python spelling of the parameter. 
 ;;
-;;But the translation between the two should be obvious.
+;; But the translation between the two should be obvious.
 
 
-;;Example: logistic regression
+;;Example: [logistic regression](https://en.wikipedia.org/wiki/Logistic_regression)
 
 (def ds (dst/tensor->dataset [[0 0 0] [1 1 1] [2 2 2]]))
 
-;;Make pipe with sklearn model 'logistic-regression'
+;; Make pipe with sklearn model 'logistic-regression'
 (def pipe
   (mm/pipeline
    (ds-mm/set-inference-target 2)
@@ -35,29 +36,27 @@
               :max-iter 100})))
 
 
-;;Train model
+;; Train model:
 (def fitted-ctx
   (pipe {:metamorph/data ds
          :metamorph/mode :fit}))
 
-;;Predict on new data
+;; Predict on new data:
 (->
  (mm/transform-pipe
   (dst/tensor->dataset [[3 4 5]])
   pipe
   fitted-ctx)
  :metamorph/data)
 
-;;Access model details via python interop (libpython-clj)
+;; Access model details via Python interop
+;; (using [libpython-clj](https://github.com/clj-python/libpython-clj)):
 (-> fitted-ctx :model :model-data :model
     (py.- coef_)
     (->jvm))
 
 
-
-
-
-;;All model attributes are as well in the context
+;; All model attributes are also included in the context.
 
 (def model-attributes
   (-> fitted-ctx :model :model-data :attributes))
@@ -73,16 +72,14 @@
 
 
 
-
-
-;;## :sklearn.classification models
+;; ## `:sklearn.classification` models
 ^:kindly/hide-code
 (render-key-info ":sklearn.classification" {:level "###"
                                             :remove-s ":sklearn.classification"
                                             :docu-doc-string-fn noj-book.utils.render-tools-sklearn/docu-doc-string})
 
 
-;;## :sklearn.regression models
+;; ## `:sklearn.regression` models
 ^:kindly/hide-code
 (render-key-info ":sklearn.regression" {:level "###"
                                         :remove-s ":sklearn.regression"})

notebooks/noj_book/smile_classification.clj

@@ -20,8 +20,8 @@
 
 
 ;; ## Smile classification models reference
-;; In the following we have a list of all model keys of Smile classification models
-;; including parameters.
+;; In the following we have a list of all model keys of
+;; [Smile](https://haifengl.github.io/) classification models, including parameters.
 ;; They can be used like this:
 
 (comment
@@ -30,8 +30,7 @@
              :param-1 0
              :param-2 1}))
 
-
-
+^:kindly/hide-code
 (render-key-info :smile.classification)
 
 ;; # Compare decision surfaces of different classification models

notebooks/noj_book/smile_others.clj

@@ -12,8 +12,8 @@
    [scicloj.ml.smile.projections]
    [noj-book.utils.render-tools :refer [render-key-info]]))
 
-;; In the following we have a list of all model keys of Smile model-like
-;; algorithms including parameters.
+;; In the following we have a list of all model keys of
+;; [Smile](https://haifengl.github.io/) model-like algorithms, including parameters.
 ;; They can be used in the same way as other models:
 (comment
   (ml/train df
@@ -22,7 +22,8 @@
              :param-2 1}))
 
 ;; Some do not support `ml/predict` and are defined as `unsupervised` learners.
-;; Clustering and PCA are in this group.
+;; Clustering and [PCA](https://en.wikipedia.org/wiki/Principal_component_analysis)
+;; are in this group.
 
 ;; ## Smile manifolds
 

notebooks/noj_book/smile_regression.clj

@@ -4,8 +4,8 @@
 ;; dependency to Noj.
 ;; [![Clojars Project](https://img.shields.io/clojars/v/org.scicloj/scicloj.ml.smile.svg)](https://clojars.org/org.scicloj/scicloj.ml.smile)
 
-;; In the following we have a list of all model keys of Smile regression models
-;; including parameters.
+;; In the following we have a list of all model keys of
+;; [Smile](https://haifengl.github.io/) regression models, including parameters.
 ;; They can be used like this:
 
 (comment