[DOC] update titanic random forest doc for decision_path
diff --git a/docs/gitbook/binaryclass/titanic_rf.md b/docs/gitbook/binaryclass/titanic_rf.md
index 89691b7..ee714f9 100644
--- a/docs/gitbook/binaryclass/titanic_rf.md
+++ b/docs/gitbook/binaryclass/titanic_rf.md
@@ -139,8 +139,6 @@
;
```
----
-
# Training
`select guess_attribute_types(pclass, name, sex, age, sibsp, parch, ticket, fare, cabin, embarked) from train limit 1;`
@@ -191,24 +189,16 @@
FROM (
SELECT
passengerid,
- -- rf_ensemble(predicted) as predicted
- -- v0.5.0 or later
rf_ensemble(predicted.value, predicted.posteriori, model_weight) as predicted
-- rf_ensemble(predicted.value, predicted.posteriori) as predicted -- avoid OOB accuracy (i.e., model_weight)
FROM (
SELECT
t.passengerid,
- -- from v0.4.1-alpha.3 to v0.4.2-rc4
- -- tree_predict(p.model_id, p.model_type, p.pred_model, t.features, ${classification}) as predicted
- -- v0.5.0 or later
p.model_weight,
tree_predict(p.model_id, p.model, t.features, "-classification") as predicted
-- tree_predict_v1(p.model_id, p.model_type, p.pred_model, t.features, ${classification}) as predicted -- to use the old model in v0.5.0 or later
FROM (
SELECT
- -- from v0.4.1-alpha.3 or v0.4.2-rc4
- -- model_id, model_type, pred_model
- -- v0.5.0 or later
model_id, model_weight, model
FROM
model_rf
@@ -285,8 +275,6 @@
[Here is an example](https://gist.github.com/myui/a83ba3795bad9b278cf8bcc59f946e2c#file-titanic-dot) plotting a decision tree using Graphviz or [Vis.js](https://viz-js.com/).
----
-
# Test by dividing training dataset
```sql
@@ -334,25 +322,17 @@
FROM (
SELECT
passengerid,
- -- rf_ensemble(predicted) as predicted
- -- v0.5.0 or later
rf_ensemble(predicted.value, predicted.posteriori, model_weight) as predicted
-- rf_ensemble(predicted.value, predicted.posteriori) as predicted -- avoid OOB accuracy (i.e., model_weight)
FROM (
SELECT
- t.passengerid,
- -- from v0.4.1-alpha.3 or v0.4.2-rc4
- -- tree_predict(p.model_id, p.model_type, p.pred_model, t.features, ${classification}) as predicted
- -- v0.5.0 or later
+ t.passengerid,
p.model_weight,
tree_predict(p.model_id, p.model, t.features, "-classification") as predicted
-- tree_predict(p.model_id, p.model, t.features, ${classification}) as predicted
-- tree_predict_v1(p.model_id, p.model_type, p.pred_model, t.features, ${classification}) as predicted -- to use the old model in v0.5.0 or later
FROM (
SELECT
- -- from v0.4.1-alpha.3 to v0.4.2-rc4
- -- model_id, model_type, pred_model
- -- v0.5.0 or later
model_id, model_weight, model
FROM
model_rf_07
@@ -363,28 +343,58 @@
group by
passengerid
) t2;
-
-create or replace view rf_submit_03 as
-select
- t.survived as actual,
- p.label as predicted,
- p.probabilities
-from
- test_rf_03 t
- JOIN predicted_rf_03 p on (t.passengerid = p.passengerid)
-;
-
-select count(1) from test_rf_03;
```
-> 260
-
```sql
-set hivevar:testcnt=260;
-
-select count(1)/${testcnt} as accuracy
-from rf_submit_03
-where actual = predicted;
+WITH rf_submit_03 as (
+ select
+ t.survived as actual,
+ p.label as predicted
+ from
+ test_rf_03 t
+ JOIN predicted_rf_03 p on (t.passengerid = p.passengerid)
+)
+select sum(if(actual=predicted,1,0))/count(1) as accuracy
+from rf_submit_03;
```
> 0.8153846153846154
+## Tracing predictions
+
+Find important attributes and conditions predicted to survive.
+
+```sql
+WITH tmp as (
+ SELECT
+ t.survived as actual,
+ decision_path(m.model_id, m.model, t.features, '-classification -no_verbose', array('pclass','name','sex','age','sibsp','parch','ticket','fare','cabin','embarked')) as path
+ FROM
+ model_rf_07 m
+ LEFT OUTER JOIN -- CROSS JOIN
+ test_rf_03 t
+)
+select
+ r.branch,
+ count(1) as cnt
+from
+ tmp l
+ LATERAL VIEW explode(array_slice(path, 0, -1)) r as branch
+where
+ -- actual = 1 and -- actual is survived
+ last_element(path) = 1 -- predicted is survived
+group by
+ r.branch
+order by
+ cnt desc
+limit 100;
+```
+
+| r.branch | cnt |
+|:-|:-|
+| sex != 0.0 | 29786 |
+| pclass != 3.0 | 18520 |
+| pclass = 3.0 | 7444 |
+| sex = 0.0 | 6494 |
+| embarked != 1.0 | 6175 |
+| ticket != 22.0 | 5560 |
+| ... | ... |
