From 34d1c60755d43cd9363e2d8e5b549d1941dea6e1 Mon Sep 17 00:00:00 2001 From: daslu Date: Sun, 5 May 2024 23:39:27 +0300 Subject: [PATCH] rerendered book --- docs/noj_book.automl.html | 212 +- docs/noj_book.interactions_ols.html | 38 +- docs/noj_book.ml_basic.html | 6 +- docs/noj_book.python.html | 5630 ++++++++++++++++- docs/noj_book.python_files/reagent2.js | 31 - docs/noj_book.python_files/reagent3.js | 267 - docs/noj_book.python_files/reagent4.js | 2300 ------- docs/noj_book.python_files/reagent5.js | 118 - docs/noj_book.python_files/reagent6.js | 150 - docs/noj_book.python_files/reagent7.js | 2 - docs/noj_book.statistics.html | 14 +- docs/noj_book.visualization.html | 2 +- docs/noj_book.visualization_files/0.csv | 40 +- ...book.visualizing_correlation_matrices.html | 2 +- docs/search.json | 18 +- 15 files changed, 5787 insertions(+), 3043 deletions(-) delete mode 100644 docs/noj_book.python_files/reagent2.js delete mode 100644 docs/noj_book.python_files/reagent3.js delete mode 100644 docs/noj_book.python_files/reagent4.js delete mode 100644 docs/noj_book.python_files/reagent5.js delete mode 100644 docs/noj_book.python_files/reagent6.js delete mode 100644 docs/noj_book.python_files/reagent7.js diff --git a/docs/noj_book.automl.html b/docs/noj_book.automl.html index 08a29d1..0a1d5cb 100644 --- a/docs/noj_book.automl.html +++ b/docs/noj_book.automl.html @@ -350,14 +350,14 @@

1.0 -3.0 2.0 0.0 +0.0 0.0 3.0 -2.0 +0.0 0.0 @@ -370,19 +370,19 @@

0.0 3.0 0.0 -0.0 +1.0 0.0 -1.0 +3.0 0.0 0.0 -0.0 +1.0 3.0 1.0 -0.0 +1.0 0.0 @@ -392,21 +392,21 @@

0.0 -1.0 +2.0 +0.0 0.0 -1.0 0.0 3.0 0.0 -1.0 +0.0 -1.0 -3.0 0.0 -1.0 +2.0 +0.0 +0.0 ... @@ -415,69 +415,69 @@

... -0.0 -2.0 -2.0 +1.0 +3.0 +1.0 0.0 1.0 3.0 -1.0 0.0 +1.0 +0.0 +3.0 1.0 -1.0 -2.0 -1.0 +0.0 -0.0 +1.0 3.0 0.0 -1.0 +0.0 -0.0 +1.0 3.0 0.0 -0.0 +1.0 0.0 3.0 -1.0 +0.0 0.0 1.0 1.0 -2.0 +0.0 1.0 0.0 -3.0 1.0 0.0 +1.0 -1.0 +0.0 2.0 0.0 -1.0 +0.0 0.0 -3.0 +2.0 0.0 0.0 0.0 -1.0 -0.0 +3.0 +2.0 0.0 @@ -487,7 +487,7 @@

:metamorph/mode :fit
#uuid "57414195-1514-43bc-bc05-f666364924a9" {:model-data {:majority-class 1.0, :distinct-labels (0.0 1.0)}, :options {:model-type :metamorph.ml/dummy-classifier}, :id #uuid "90771c94-150a-4d39-ae15-3eb88d9fb897", :feature-columns [:sex :pclass :embarked], :target-columns [:survived], :target-categorical-maps {:survived #tech.v3.dataset.categorical.CategoricalMap{:lookup-table {"no" 0, "yes" 1}, :src-column :survived, :result-datatype :float64}}, :scicloj.metamorph.ml/unsupervised? nil}

}

+
:metamorph/mode :fit
#uuid "63263b11-3fbf-4c9e-8795-3993c63dec1b" {:model-data {:majority-class 1.0, :distinct-labels (0.0 1.0)}, :options {:model-type :metamorph.ml/dummy-classifier}, :id #uuid "36f54c5c-110f-4076-913b-687984de2539", :feature-columns [:sex :pclass :embarked], :target-columns [:survived], :target-categorical-maps {:survived #tech.v3.dataset.categorical.CategoricalMap{:lookup-table {"no" 0, "yes" 1}, :src-column :survived, :result-datatype :float64}}, :scicloj.metamorph.ml/unsupervised? nil}

}

(keys ctx-after-train)
@@ -495,7 +495,7 @@ 

(:metamorph/data
  :metamorph/mode
- #uuid "57414195-1514-43bc-bc05-f666364924a9")
+ #uuid "63263b11-3fbf-4c9e-8795-3993c63dec1b")

This context map has the “data”, the “mode” and an UUID for each operation (we had only one in this pipeline)

@@ -515,14 +515,14 @@

1.0 -3.0 2.0 0.0 +0.0 0.0 3.0 -2.0 +0.0 0.0 @@ -535,19 +535,19 @@

0.0 3.0 0.0 -0.0 +1.0 0.0 -1.0 +3.0 0.0 0.0 -0.0 +1.0 3.0 1.0 -0.0 +1.0 0.0 @@ -557,21 +557,21 @@

0.0 -1.0 +2.0 +0.0 0.0 -1.0 0.0 3.0 0.0 -1.0 +0.0 -1.0 -3.0 0.0 -1.0 +2.0 +0.0 +0.0 ... @@ -580,69 +580,69 @@

... -0.0 -2.0 -2.0 +1.0 +3.0 +1.0 0.0 1.0 3.0 -1.0 0.0 +1.0 +0.0 +3.0 1.0 -1.0 -2.0 -1.0 +0.0 -0.0 +1.0 3.0 0.0 -1.0 +0.0 -0.0 +1.0 3.0 0.0 -0.0 +1.0 0.0 3.0 -1.0 +0.0 0.0 1.0 1.0 -2.0 +0.0 1.0 0.0 -3.0 1.0 0.0 +1.0 -1.0 +0.0 2.0 0.0 -1.0 +0.0 0.0 -3.0 +2.0 0.0 0.0 0.0 -1.0 -0.0 +3.0 +2.0 0.0 @@ -650,7 +650,7 @@

:fit 

{:model-data {:majority-class 1.0, :distinct-labels (0.0 1.0)},
  :options {:model-type :metamorph.ml/dummy-classifier},
- :id #uuid "90771c94-150a-4d39-ae15-3eb88d9fb897",
+ :id #uuid "36f54c5c-110f-4076-913b-687984de2539",
  :feature-columns [:sex :pclass :embarked],
  :target-columns [:survived],
  :target-categorical-maps
@@ -776,7 +776,7 @@ 

 

-
#uuid "57414195-1514-43bc-bc05-f666364924a9"

+
#uuid "63263b11-3fbf-4c9e-8795-3993c63dec1b"

 

 

 

@@ -817,33 +817,33 @@ 

-0.0
-3.0
+1.0
+2.0
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-1.0
-1.0
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+0.0
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-1.0
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-0.0
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-0.0
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@@ -857,8 +857,8 @@ 
2.0
 
 
-0.0
-2.0
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@@ -872,48 +872,48 @@ 
...
 
 
-0.0
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-1.0
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@@ -937,7 +937,7 @@ 
:model-data {:majority-class 1.0, :distinct-labels (0.0 1.0)}
-
:id #uuid "90771c94-150a-4d39-ae15-3eb88d9fb897"
+
:id #uuid "36f54c5c-110f-4076-913b-687984de2539"
@@ -960,25 +960,25 @@

-

+ - + - + - + - + @@ -987,7 +987,7 @@

0.0

- + @@ -1002,19 +1002,19 @@

0.0

- + - + - + - + - + @@ -1236,7 +1236,7 @@

:metamorph/mode :fit
#uuid "7e4d6419-de8e-4c93-8f3c-a77b4e40f5a8" {:model-data {:majority-class 1, :distinct-labels (0.0 1.0)}, :options {:model-type :metamorph.ml/dummy-classifier}, :id #uuid "09b4ae8f-3479-4d8f-8c38-cc3324ac265e", :feature-columns [:sex :pclass :embarked], :target-columns [:survived], :target-categorical-maps {:survived #tech.v3.dataset.categorical.CategoricalMap{:lookup-table {"no" 0, "yes" 1}, :src-column :survived, :result-datatype :float64}}, :scicloj.metamorph.ml/unsupervised? nil}

}

+
:metamorph/mode :fit
#uuid "66756a3f-1849-48ae-9217-684bc198857d" {:model-data {:majority-class 1, :distinct-labels (0.0 1.0)}, :options {:model-type :metamorph.ml/dummy-classifier}, :id #uuid "0aa0639a-66ea-4601-b7c1-e26a8ac92d8b", :feature-columns [:sex :pclass :embarked], :target-columns [:survived], :target-categorical-maps {:survived #tech.v3.dataset.categorical.CategoricalMap{:lookup-table {"no" 0, "yes" 1}, :src-column :survived, :result-datatype :float64}}, :scicloj.metamorph.ml/unsupervised? nil}

}

To show the power of pipelines, I start with doing the simplest possible pipeline, and expand then on it.

we can already chain train and test with usual functions:

diff --git a/docs/noj_book.interactions_ols.html b/docs/noj_book.interactions_ols.html index edc5bb1..4ad04c1 100644 --- a/docs/noj_book.interactions_ols.html +++ b/docs/noj_book.interactions_ols.html @@ -348,19 +348,19 @@

Residuals: Min 1Q Median 3Q Max - -10.1808 -1.2477 0.3855 1.4717 3.5701 + -5.7074 -0.9998 0.3252 1.1840 3.6785 Coefficients: Estimate Std. Error t value Pr(>|t|) -Intercept 3.2517 0.4605 7.0615 0.0000 *** -youtube 0.0468 0.0018 26.4844 0.0000 *** -facebook 0.1854 0.0106 17.4187 0.0000 *** +Intercept 3.3838 0.3901 8.6751 0.0000 *** +youtube 0.0438 0.0016 27.2563 0.0000 *** +facebook 0.2107 0.0090 23.4578 0.0000 *** --------------------------------------------------------------------- Significance codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 -Residual standard error: 2.1636 on 130 degrees of freedom -Multiple R-squared: 0.8857, Adjusted R-squared: 0.8840 -F-statistic: 503.8707 on 3 and 130 DF, p-value: 5.801e-62 +Residual standard error: 1.8727 on 130 degrees of freedom +Multiple R-squared: 0.9216, Adjusted R-squared: 0.9204 +F-statistic: 764.3823 on 3 and 130 DF, p-value: 1.319e-72

We have the following metrics:

\(RMSE\)

@@ -368,14 +368,14 @@ 

(-> evaluations flatten first :test-transform :metric)
-
1.7293393770640264
+
2.4136890070958295

\(R^2\)

(-> evaluations flatten first :test-transform :other-metrices first :metric)
-
0.9223737393827188
+
0.8114211930370409
@@ -407,20 +407,20 @@

Residuals: Min 1Q Median 3Q Max - -4.5744 -0.5438 0.2698 0.6643 1.7632 + -7.1135 -0.5183 0.2392 0.7820 1.8570 Coefficients: Estimate Std. Error t value Pr(>|t|) -Intercept 7.4629 0.3168 23.5596 0.0000 *** -youtube 0.0220 0.0017 13.0535 0.0000 *** -facebook 0.0567 0.0098 5.7697 0.0000 *** -youtube*facebook 0.0008 0.0000 15.8067 0.0000 *** +Intercept 8.2880 0.4010 20.6681 0.0000 *** +youtube 0.0177 0.0020 8.8557 0.0000 *** +facebook 0.0145 0.0126 1.1561 0.2498 +youtube*facebook 0.0010 0.0001 15.9127 0.0000 *** --------------------------------------------------------------------- Significance codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 -Residual standard error: 1.0261 on 129 degrees of freedom -Multiple R-squared: 0.9734, Adjusted R-squared: 0.9728 -F-statistic: 1573.5134 on 4 and 129 DF, p-value: 2.287e-101 +Residual standard error: 1.2082 on 129 degrees of freedom +Multiple R-squared: 0.9613, Adjusted R-squared: 0.9604 +F-statistic: 1068.5077 on 4 and 129 DF, p-value: 7.058e-91

As the multiplcation of youtube*facebook is as well statistically relevant, it suggests that there is indeed an interaction between these 2 predictor variables youtube and facebook.

\(RMSE\)

@@ -428,14 +428,14 @@ 

(-> evaluations flatten first :test-transform :metric)
-
1.3886192343479014
+
1.0326921147850543

\(R^2\)

(-> evaluations flatten first :test-transform :other-metrices first :metric)
-
0.9526434225525324
+
0.9797845745830085

\(RMSE\) and \(R^2\) of the intercation model are sligtly better.

These results suggest that the model with the interaction term is better than the model that contains only main effects. So, for this specific data, we should go for the model with the interaction model.

diff --git a/docs/noj_book.ml_basic.html b/docs/noj_book.ml_basic.html index 4bbcd70..fb96280 100644 --- a/docs/noj_book.ml_basic.html +++ b/docs/noj_book.ml_basic.html @@ -1429,9 +1429,9 @@

reverse)
-
({:predictor :sex, :importance 46.78962303978025}
- {:predictor :pclass, :importance 10.161034312486382}
- {:predictor :embarked, :importance 1.9200954892919857})
+
({:predictor :sex, :importance 43.49550702245125}
+ {:predictor :pclass, :importance 9.875056067188698}
+ {:predictor :embarked, :importance 2.0275170176104824})

we can see that :sex is more important to predict :survived then :pclass and :embark

diff --git a/docs/noj_book.python.html b/docs/noj_book.python.html index 14dd0c9..9df1dea 100644 --- a/docs/noj_book.python.html +++ b/docs/noj_book.python.html @@ -259,12 +259,6 @@

7  - - - - - -

author: Daniel Slutsky

(ns noj-book.python
@@ -300,14 +294,1196 @@ 
   (:x sine-data)
    (:y sine-data)))
-
+ + + + + + + + 2024-05-05T23:34:58.230643 + image/svg+xml + + + Matplotlib v3.7.1, https://matplotlib.org/ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + 
(vis.python/pyplot
  #(matplotlib.pyplot/plot
    (:x sine-data)
    (:y sine-data)))
-
+ + + + + + + + 2024-05-05T23:34:58.341506 + image/svg+xml + + + Matplotlib v3.7.1, https://matplotlib.org/ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +

https://seaborn.pydata.org/tutorial/introduction

(let [tips (sns/load_dataset "tips")]
@@ -321,7 +1497,4443 @@ 
                 :style "smoker"
                  :size "size")))
-
+ + + + + + + + 2024-05-05T23:34:58.840168 + image/svg+xml + + + Matplotlib v3.7.1, https://matplotlib.org/ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + 
:bye
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