From b080cc76061dd72aa355f951bb8138f7074de4dc Mon Sep 17 00:00:00 2001
From: daslu Datasets
Visualizing correlation matrices (experimental π ) - DRAFT
ctx-after-train
{
{
1.0 | +0.0 | 3.0 | 0.0 | 0.0 | ||
1.0 | -1.0 | +0.0 | +3.0 | 0.0 | 1.0 | |
1.0 | +0.0 | 3.0 | 0.0 | 0.0 | ||
1.0 | +2.0 | 0.0 | -3.0 | -0.0 | -0.0 | +1.0 |
0.0 | +1.0 | 3.0 | 0.0 | 0.0 | ||
0.0 | -3.0 | +2.0 | 0.0 | 0.0 | ||
1.0 | +0.0 | 3.0 | -1.0 | -1.0 | +0.0 | +0.0 |
0.0 | +1.0 | 3.0 | -0.0 | +2.0 | 1.0 | |
1.0 | -3.0 | -0.0 | -0.0 | +1.0 | +2.0 | +1.0 |
0.0 | -3.0 | -0.0 | +2.0 | +2.0 | 0.0 | |
0.0 | 1.0 | -1.0 | -2.0 | -1.0 | +0.0 | +0.0 |
1.0 | 1.0 | -0.0 | +2.0 | 1.0 | ||
0.0 | 2.0 | -2.0 | +0.0 | 0.0 | ||
1.0 | +0.0 | 3.0 | 0.0 | -1.0 | +0.0 | |
1.0 | +1.0 | 0.0 | -3.0 | -0.0 | -0.0 | +1.0 |
0.0 | -2.0 | +3.0 | 0.0 | 0.0 | ||
0.0 | 3.0 | -1.0 | +0.0 | 0.0 | ||
1.0 | -2.0 | 0.0 | 1.0 | +0.0 | +0.0 | |
0.0 | -3.0 | +2.0 | 0.0 | 0.0 |
1.0 | +0.0 | 3.0 | 0.0 | 0.0 | ||
1.0 | -1.0 | +0.0 | +3.0 | 0.0 | 1.0 | |
1.0 | +0.0 | 3.0 | 0.0 | 0.0 | ||
1.0 | +2.0 | 0.0 | -3.0 | -0.0 | -0.0 | +1.0 |
0.0 | +1.0 | 3.0 | 0.0 | 0.0 | ||
0.0 | -3.0 | +2.0 | 0.0 | 0.0 | ||
1.0 | +0.0 | 3.0 | -1.0 | -1.0 | +0.0 | +0.0 |
0.0 | +1.0 | 3.0 | -0.0 | +2.0 | 1.0 | |
1.0 | -3.0 | -0.0 | -0.0 | +1.0 | +2.0 | +1.0 |
0.0 | -3.0 | -0.0 | +2.0 | +2.0 | 0.0 | |
0.0 | 1.0 | -1.0 | -2.0 | -1.0 | +0.0 | +0.0 |
1.0 | 1.0 | -0.0 | +2.0 | 1.0 | ||
0.0 | 2.0 | -2.0 | +0.0 | 0.0 | ||
1.0 | +0.0 | 3.0 | 0.0 | -1.0 | +0.0 | |
1.0 | +1.0 | 0.0 | -3.0 | -0.0 | -0.0 | +1.0 |
0.0 | -2.0 | +3.0 | 0.0 | 0.0 | ||
0.0 | 3.0 | -1.0 | +0.0 | 0.0 | ||
1.0 | -2.0 | 0.0 | 1.0 | +0.0 | +0.0 | |
0.0 | -3.0 | +2.0 | 0.0 | 0.0 |
-
+
|
{ -
+
-0.0 |
-2.0 |
+1.0 |
+3.0 |
0.0 |
0.0 |
-3.0 |
1.0 |
+2.0 |
+0.0 |
0.01.0 |
-2.0 |
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+3.0 |
+1.0 |
0.0 |
1.0 |
-3.0 |
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+3.0 |
+2.0 |
1.0 |
-1.0 |
+0.0 |
+3.0 |
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1.0 |
+0.0 |
3.0 |
0.0 |
0.0 |
+1.0 |
+1.0 |
2.0 |
-0.0 |
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+0.0 |
1.0 |
2.0 |
0.0 |
-3.0 |
-0.0 |
+1.0 |
+1.0 |
+2.0 |
0.0 |
+1.0 |
+1.0 |
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-0.0 |
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| 0.0 | 1.0 | -2.0 | +0.0 | 1.0 | -1.0 | +2.0 | 0.0 | 0.0 | -3.0 | -0.0 | +2.0 | +2.0 | ... | @@ -873,44 +873,44 @@0.0 | 3.0 | -1.0 | +0.0 | 1.0 | -1.0 | 2.0 | +0.0 | 0.0 | @@ -919,13 +919,13 @@0.0 | -2.0 | +3.0 | 0.0 |
:model-data {:majority-class 1.0, :distinct-labels (0.0 1.0)}
:id #uuid "2dd95fc5-096f-46c2-9d20-3ef230c97dc3"
+:id #uuid "ad1a8ebd-6247-47a4-991f-49bb45043570"
0.0 | +1.0 |
0.0 | |
0.0 | -|
1.0 | -|
1.0 | |
1.0 | +|
0.0 | +|
... | |
1.0 | +0.0 |
0.0 | @@ -1009,13 +1009,13 @@|
0.0 | +1.0 |
1.0 | |
0.0 | +1.0 |
1.0 | @@ -1024,7 +1024,7 @@|
1.0 | +0.0 |
train-ctx
{
{
[:sex :pclass :embarked] | 0.81107726 | -{:model-type :scicloj.ml.tribuo/classification, | +{:model-type :smile.classification/ada-boost} |
[:sex :pclass :embarked] | +0.81107726 | +{:model-type :scicloj.ml.tribuo/classification, | +
:tribuo-components | ||
[{:name trainer, | ||
:type org.tribuo.classification.dtree.CARTClassificationTrainer, | ||
:properties | ||
{:maxDepth 8, | ||
:useRandomSplitPoints false, | ||
:fractionFeaturesInSplit 0.5}}], | ||
:tribuo-trainer-name trainer} | ||
[:sex :pclass :embarked] | -0.81107726 | -{:model-type :smile.classification/ada-boost} | -
[:sex] | 0.78633276 | -{:model-type :smile.classification/logistic-regression} | -
[:sex] | -0.78633276 | {:model-type :scicloj.ml.tribuo/classification, |
:tribuo-components | ||
[{:name trainer, | ||
:type org.tribuo.classification.dtree.CARTClassificationTrainer, | ||
:properties | ||
{:maxDepth 8, | ||
:useRandomSplitPoints false, | ||
:fractionFeaturesInSplit 0.5}}], | ||
:tribuo-trainer-name trainer} | ||
[:sex :embarked] | +||
[:sex] | 0.78633276 | {:model-type :smile.classification/ada-boost} |
[:sex :pclass] | +0.78633276 | +{:model-type :smile.classification/logistic-regression} | +
We have the following metrics:
\(RMSE\)
@@ -374,14 +374,14 @@-> evaluations flatten first :test-transform :metric) (
1.9921201677612856
1.727635715123888
\(R^2\)
-> evaluations flatten first :test-transform :other-metrices first :metric) (
0.8911583564973837
0.9138890196777525
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.
\(RMSE\)
@@ -434,14 +434,14 @@-> evaluations flatten first :test-transform :metric) (
0.788376113686339
1.02489232563229
\(R^2\)
-> evaluations flatten first :test-transform :other-metrices first :metric) (
0.9837989524603392
0.9711197427339897
\(RMSE\) 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.known_issues.html b/docs/noj_book.known_issues.html index 0dfc069..bff9e33 100644 --- a/docs/noj_book.known_issues.html +++ b/docs/noj_book.known_issues.html @@ -157,19 +157,19 @@ split
{
{