Why log-transform to normal distribution for decision trees?
On page 304 of chapter 8 of An Introduction to Statistical Learning with Applications in R (James et al.), the authors say:
We use the Hitters data set to predict a baseball player’s Salary based on Years (the number of years that he has played in the major leagues) and Hits (the number of hits that he made in the previous year). We first remove observations that are missing Salary values, and log-transform Salary so that its distribution has more of a typical bell-shape. (Recall that Salary is measured in thousands of dollars.)
No additional motivation for the log-transform is given. Being that the data are being fed into decision tree algorithms, why was it important to force the data into a normal distribution? I thought most/all decision tree algorithms were invariant to scale changes.
machine-learning cart
edited 2 hours ago
Sycorax
38.9k1197195
asked 2 hours ago
jss367
1084
New contributor
jss367 is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
add a comment |
On page 304 of chapter 8 of An Introduction to Statistical Learning with Applications in R (James et al.), the authors say:
We use the Hitters data set to predict a baseball player’s Salary based on Years (the number of years that he has played in the major leagues) and Hits (the number of hits that he made in the previous year). We first remove observations that are missing Salary values, and log-transform Salary so that its distribution has more of a typical bell-shape. (Recall that Salary is measured in thousands of dollars.)
No additional motivation for the log-transform is given. Being that the data are being fed into decision tree algorithms, why was it important to force the data into a normal distribution? I thought most/all decision tree algorithms were invariant to scale changes.
machine-learning cart
edited 2 hours ago
Sycorax
38.9k1197195
asked 2 hours ago
jss367
1084
New contributor
jss367 is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
add a comment |
On page 304 of chapter 8 of An Introduction to Statistical Learning with Applications in R (James et al.), the authors say:
We use the Hitters data set to predict a baseball player’s Salary based on Years (the number of years that he has played in the major leagues) and Hits (the number of hits that he made in the previous year). We first remove observations that are missing Salary values, and log-transform Salary so that its distribution has more of a typical bell-shape. (Recall that Salary is measured in thousands of dollars.)
No additional motivation for the log-transform is given. Being that the data are being fed into decision tree algorithms, why was it important to force the data into a normal distribution? I thought most/all decision tree algorithms were invariant to scale changes.
machine-learning cart
edited 2 hours ago
Sycorax
38.9k1197195
asked 2 hours ago
jss367
1084
New contributor
jss367 is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
On page 304 of chapter 8 of An Introduction to Statistical Learning with Applications in R (James et al.), the authors say:
We use the Hitters data set to predict a baseball player’s Salary based on Years (the number of years that he has played in the major leagues) and Hits (the number of hits that he made in the previous year). We first remove observations that are missing Salary values, and log-transform Salary so that its distribution has more of a typical bell-shape. (Recall that Salary is measured in thousands of dollars.)
No additional motivation for the log-transform is given. Being that the data are being fed into decision tree algorithms, why was it important to force the data into a normal distribution? I thought most/all decision tree algorithms were invariant to scale changes.
machine-learning cart
machine-learning cart
edited 2 hours ago
Sycorax
38.9k1197195
asked 2 hours ago
jss367
1084
New contributor
jss367 is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
edited 2 hours ago
Sycorax
38.9k1197195
asked 2 hours ago
jss367
1084
New contributor
jss367 is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
edited 2 hours ago
Sycorax
38.9k1197195
edited 2 hours ago
Sycorax
38.9k1197195
edited 2 hours ago
Sycorax
38.9k1197195
38.9k1197195
asked 2 hours ago
jss367
1084
New contributor
jss367 is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
asked 2 hours ago
jss367
1084
asked 2 hours ago
jss367
1084
1084
New contributor
jss367 is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
New contributor
jss367 is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
jss367 is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
add a comment |
add a comment |
1 Answer
1
active
oldest
votes
In this case, the salary is the target of the decision tree, not one of the features (independent variables/predictors). You are correct that decision trees are insensitive to the scale of the predictors, but since I suspect there are a small number of extremely large salaries, transforming the salaries might improve predictions because loss functions which minimize square error will not be so strongly influenced by these large values.
answered 2 hours ago
Sycorax
38.9k1197195
add a comment |
Your Answer
StackExchange.ifUsing("editor", function () {
return StackExchange.using("mathjaxEditing", function () {
StackExchange.MarkdownEditor.creationCallbacks.add(function (editor, postfix) {
StackExchange.mathjaxEditing.prepareWmdForMathJax(editor, postfix, [["$", "$"], ["\\(","\\)"]]);
});
});
}, "mathjax-editing");
StackExchange.ready(function() {
var channelOptions = {
tags: "".split(" "),
id: "65"
};
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: false,
noModals: true,
showLowRepImageUploadWarning: true,
reputationToPostImages: null,
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
});
}
});
jss367 is a new contributor. Be nice, and check out our Code of Conduct.
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%2fstats.stackexchange.com%2fquestions%2f385231%2fwhy-log-transform-to-normal-distribution-for-decision-trees%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
In this case, the salary is the target of the decision tree, not one of the features (independent variables/predictors). You are correct that decision trees are insensitive to the scale of the predictors, but since I suspect there are a small number of extremely large salaries, transforming the salaries might improve predictions because loss functions which minimize square error will not be so strongly influenced by these large values.
answered 2 hours ago
Sycorax
38.9k1197195
add a comment |
In this case, the salary is the target of the decision tree, not one of the features (independent variables/predictors). You are correct that decision trees are insensitive to the scale of the predictors, but since I suspect there are a small number of extremely large salaries, transforming the salaries might improve predictions because loss functions which minimize square error will not be so strongly influenced by these large values.
answered 2 hours ago
Sycorax
38.9k1197195
add a comment |
In this case, the salary is the target of the decision tree, not one of the features (independent variables/predictors). You are correct that decision trees are insensitive to the scale of the predictors, but since I suspect there are a small number of extremely large salaries, transforming the salaries might improve predictions because loss functions which minimize square error will not be so strongly influenced by these large values.
answered 2 hours ago
Sycorax
38.9k1197195
In this case, the salary is the target of the decision tree, not one of the features (independent variables/predictors). You are correct that decision trees are insensitive to the scale of the predictors, but since I suspect there are a small number of extremely large salaries, transforming the salaries might improve predictions because loss functions which minimize square error will not be so strongly influenced by these large values.
answered 2 hours ago
Sycorax
38.9k1197195
answered 2 hours ago
Sycorax
38.9k1197195
answered 2 hours ago
Sycorax
38.9k1197195
answered 2 hours ago
Sycorax
38.9k1197195
38.9k1197195
add a comment |
add a comment |
jss367 is a new contributor. Be nice, and check out our Code of Conduct.
jss367 is a new contributor. Be nice, and check out our Code of Conduct.
jss367 is a new contributor. Be nice, and check out our Code of Conduct.
jss367 is a new contributor. Be nice, and check out our Code of Conduct.
Thanks for contributing an answer to Cross Validated!
- 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.
Use MathJax to format equations. MathJax reference.
To learn more, see our tips on writing great answers.
Some of your past answers have not been well-received, and you're in danger of being blocked from answering.
Please pay close attention to the following guidance:
- 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%2fstats.stackexchange.com%2fquestions%2f385231%2fwhy-log-transform-to-normal-distribution-for-decision-trees%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
