Access trees and nodes from LightGBM model
In sci-kit learn, it's possible to access the entire tree structure, that is, each node of the tree. This allows to explore the attributes used at each split of the tree and which values are used for the test
The binary tree structure has 5 nodes and has the following tree structure:
node=0 test node: go to node 1 if X[:, 3] <= 0.800000011920929 else to node 2.
node=1 leaf node.
node=2 test node: go to node 3 if X[:, 2] <= 4.950000047683716 else to node 4.
node=3 leaf node.
node=4 leaf node.
Rules used to predict sample 0:
decision id node 0 : (X_test[0, 3] (= 2.4) > 0.800000011920929)
decision id node 2 : (X_test[0, 2] (= 5.1) > 4.950000047683716)
For the Random Forest, you can obtain the same information by looping across all the decision trees
for tree in model.estimators_:
# extract info from tree
Can the same information be extracted from a LightGBM model? That is, can you access: a) every tree and b) every node of a tree?
nodes random-forest decision-tree lightgbm
asked Nov 13 '18 at 12:17
Titus PulloTitus Pullo
1,29872848
add a comment |
In sci-kit learn, it's possible to access the entire tree structure, that is, each node of the tree. This allows to explore the attributes used at each split of the tree and which values are used for the test
The binary tree structure has 5 nodes and has the following tree structure:
node=0 test node: go to node 1 if X[:, 3] <= 0.800000011920929 else to node 2.
node=1 leaf node.
node=2 test node: go to node 3 if X[:, 2] <= 4.950000047683716 else to node 4.
node=3 leaf node.
node=4 leaf node.
Rules used to predict sample 0:
decision id node 0 : (X_test[0, 3] (= 2.4) > 0.800000011920929)
decision id node 2 : (X_test[0, 2] (= 5.1) > 4.950000047683716)
For the Random Forest, you can obtain the same information by looping across all the decision trees
for tree in model.estimators_:
# extract info from tree
Can the same information be extracted from a LightGBM model? That is, can you access: a) every tree and b) every node of a tree?
nodes random-forest decision-tree lightgbm
asked Nov 13 '18 at 12:17
Titus PulloTitus Pullo
1,29872848
add a comment |
In sci-kit learn, it's possible to access the entire tree structure, that is, each node of the tree. This allows to explore the attributes used at each split of the tree and which values are used for the test
The binary tree structure has 5 nodes and has the following tree structure:
node=0 test node: go to node 1 if X[:, 3] <= 0.800000011920929 else to node 2.
node=1 leaf node.
node=2 test node: go to node 3 if X[:, 2] <= 4.950000047683716 else to node 4.
node=3 leaf node.
node=4 leaf node.
Rules used to predict sample 0:
decision id node 0 : (X_test[0, 3] (= 2.4) > 0.800000011920929)
decision id node 2 : (X_test[0, 2] (= 5.1) > 4.950000047683716)
For the Random Forest, you can obtain the same information by looping across all the decision trees
for tree in model.estimators_:
# extract info from tree
Can the same information be extracted from a LightGBM model? That is, can you access: a) every tree and b) every node of a tree?
nodes random-forest decision-tree lightgbm
asked Nov 13 '18 at 12:17
Titus PulloTitus Pullo
1,29872848
In sci-kit learn, it's possible to access the entire tree structure, that is, each node of the tree. This allows to explore the attributes used at each split of the tree and which values are used for the test
The binary tree structure has 5 nodes and has the following tree structure:
node=0 test node: go to node 1 if X[:, 3] <= 0.800000011920929 else to node 2.
node=1 leaf node.
node=2 test node: go to node 3 if X[:, 2] <= 4.950000047683716 else to node 4.
node=3 leaf node.
node=4 leaf node.
Rules used to predict sample 0:
decision id node 0 : (X_test[0, 3] (= 2.4) > 0.800000011920929)
decision id node 2 : (X_test[0, 2] (= 5.1) > 4.950000047683716)
For the Random Forest, you can obtain the same information by looping across all the decision trees
for tree in model.estimators_:
# extract info from tree
Can the same information be extracted from a LightGBM model? That is, can you access: a) every tree and b) every node of a tree?
nodes random-forest decision-tree lightgbm
nodes random-forest decision-tree lightgbm
asked Nov 13 '18 at 12:17
Titus PulloTitus Pullo
1,29872848
asked Nov 13 '18 at 12:17
Titus PulloTitus Pullo
1,29872848
asked Nov 13 '18 at 12:17
Titus PulloTitus Pullo
1,29872848
asked Nov 13 '18 at 12:17
Titus PulloTitus Pullo
1,29872848
asked Nov 13 '18 at 12:17
Titus PulloTitus Pullo
1,29872848
1,29872848
add a comment |
add a comment |
1 Answer
1
active
oldest
votes
LightGBM has almost the same functions with XGBoost; sometimes I even go to the XGBoost documentation to find the functions of LightGBM. You can search for how it is done in XGBoost or you can refer directly to: https://github.com/Microsoft/LightGBM/issues/845
Also, LightGBM has a sklearn wrapper, it is probably possible to use the sklearn structure on the model you train as the way you shared. You may want to have a look at: https://lightgbm.readthedocs.io/en/latest/_modules/lightgbm/sklearn.html
Hope I could help, please do not hesitate to write if not resolved; I will go deeper in details.
answered Nov 16 '18 at 11:47
Ugur MULUKUgur MULUK
2566
add a comment |
Your Answer
StackExchange.ifUsing("editor", function () {
StackExchange.using("externalEditor", function () {
StackExchange.using("snippets", function () {
StackExchange.snippets.init();
});
});
}, "code-snippets");
StackExchange.ready(function() {
var channelOptions = {
tags: "".split(" "),
id: "1"
};
initTagRenderer("".split(" "), "".split(" "), channelOptions);
StackExchange.using("externalEditor", function() {
// Have to fire editor after snippets, if snippets enabled
if (StackExchange.settings.snippets.snippetsEnabled) {
StackExchange.using("snippets", function() {
createEditor();
});
}
else {
createEditor();
}
});
function createEditor() {
StackExchange.prepareEditor({
heartbeatType: 'answer',
autoActivateHeartbeat: false,
convertImagesToLinks: true,
noModals: true,
showLowRepImageUploadWarning: true,
reputationToPostImages: 10,
bindNavPrevention: true,
postfix: "",
imageUploader: {
brandingHtml: "Powered by u003ca class="icon-imgur-white" href="https://imgur.com/"u003eu003c/au003e",
contentPolicyHtml: "User contributions licensed under u003ca href="https://creativecommons.org/licenses/by-sa/3.0/"u003ecc by-sa 3.0 with attribution requiredu003c/au003e u003ca href="https://stackoverflow.com/legal/content-policy"u003e(content policy)u003c/au003e",
allowUrls: true
},
onDemand: true,
discardSelector: ".discard-answer"
,immediatelyShowMarkdownHelp:true
});
}
});
Sign up or log in
StackExchange.ready(function () {
StackExchange.helpers.onClickDraftSave('#login-link');
});
Sign up using Google
Sign up using Facebook
Sign up using Email and Password
Post as a guest
Required, but never shown
StackExchange.ready(
function () {
StackExchange.openid.initPostLogin('.new-post-login', 'https%3a%2f%2fstackoverflow.com%2fquestions%2f53280845%2faccess-trees-and-nodes-from-lightgbm-model%23new-answer', 'question_page');
}
);
Post as a guest
Required, but never shown
1 Answer
1
active
oldest
votes
1 Answer
1
active
oldest
votes
active
oldest
votes
active
oldest
votes
LightGBM has almost the same functions with XGBoost; sometimes I even go to the XGBoost documentation to find the functions of LightGBM. You can search for how it is done in XGBoost or you can refer directly to: https://github.com/Microsoft/LightGBM/issues/845
Also, LightGBM has a sklearn wrapper, it is probably possible to use the sklearn structure on the model you train as the way you shared. You may want to have a look at: https://lightgbm.readthedocs.io/en/latest/_modules/lightgbm/sklearn.html
Hope I could help, please do not hesitate to write if not resolved; I will go deeper in details.
answered Nov 16 '18 at 11:47
Ugur MULUKUgur MULUK
2566
add a comment |
LightGBM has almost the same functions with XGBoost; sometimes I even go to the XGBoost documentation to find the functions of LightGBM. You can search for how it is done in XGBoost or you can refer directly to: https://github.com/Microsoft/LightGBM/issues/845
Also, LightGBM has a sklearn wrapper, it is probably possible to use the sklearn structure on the model you train as the way you shared. You may want to have a look at: https://lightgbm.readthedocs.io/en/latest/_modules/lightgbm/sklearn.html
Hope I could help, please do not hesitate to write if not resolved; I will go deeper in details.
answered Nov 16 '18 at 11:47
Ugur MULUKUgur MULUK
2566
add a comment |
LightGBM has almost the same functions with XGBoost; sometimes I even go to the XGBoost documentation to find the functions of LightGBM. You can search for how it is done in XGBoost or you can refer directly to: https://github.com/Microsoft/LightGBM/issues/845
Also, LightGBM has a sklearn wrapper, it is probably possible to use the sklearn structure on the model you train as the way you shared. You may want to have a look at: https://lightgbm.readthedocs.io/en/latest/_modules/lightgbm/sklearn.html
Hope I could help, please do not hesitate to write if not resolved; I will go deeper in details.
answered Nov 16 '18 at 11:47
Ugur MULUKUgur MULUK
2566
LightGBM has almost the same functions with XGBoost; sometimes I even go to the XGBoost documentation to find the functions of LightGBM. You can search for how it is done in XGBoost or you can refer directly to: https://github.com/Microsoft/LightGBM/issues/845
Also, LightGBM has a sklearn wrapper, it is probably possible to use the sklearn structure on the model you train as the way you shared. You may want to have a look at: https://lightgbm.readthedocs.io/en/latest/_modules/lightgbm/sklearn.html
Hope I could help, please do not hesitate to write if not resolved; I will go deeper in details.
answered Nov 16 '18 at 11:47
Ugur MULUKUgur MULUK
2566
answered Nov 16 '18 at 11:47
Ugur MULUKUgur MULUK
2566
answered Nov 16 '18 at 11:47
Ugur MULUKUgur MULUK
2566
answered Nov 16 '18 at 11:47
Ugur MULUKUgur MULUK
2566
2566
add a comment |
add a comment |
Thanks for contributing an answer to Stack Overflow!
- Please be sure to answer the question. Provide details and share your research!
But avoid …
- Asking for help, clarification, or responding to other answers.
- Making statements based on opinion; back them up with references or personal experience.
To learn more, see our tips on writing great answers.
Sign up or log in
StackExchange.ready(function () {
StackExchange.helpers.onClickDraftSave('#login-link');
});
Sign up using Google
Sign up using Facebook
Sign up using Email and Password
Post as a guest
Required, but never shown
StackExchange.ready(
function () {
StackExchange.openid.initPostLogin('.new-post-login', 'https%3a%2f%2fstackoverflow.com%2fquestions%2f53280845%2faccess-trees-and-nodes-from-lightgbm-model%23new-answer', 'question_page');
}
);
Post as a guest
Required, but never shown
Sign up or log in
StackExchange.ready(function () {
StackExchange.helpers.onClickDraftSave('#login-link');
});
Sign up using Google
Sign up using Facebook
Sign up using Email and Password
Post as a guest
Required, but never shown
Sign up or log in
StackExchange.ready(function () {
StackExchange.helpers.onClickDraftSave('#login-link');
});
Sign up using Google
Sign up using Facebook
Sign up using Email and Password
Post as a guest
Required, but never shown
Sign up or log in
StackExchange.ready(function () {
StackExchange.helpers.onClickDraftSave('#login-link');
});
Sign up using Google
Sign up using Facebook
Sign up using Email and Password
Sign up using Google
Sign up using Facebook
Sign up using Email and Password
Post as a guest
Required, but never shown
Required, but never shown
Required, but never shown
Required, but never shown
Required, but never shown
Required, but never shown
Required, but never shown
Required, but never shown
Required, but never shown
