Tatiana belyukina #11
Open
Conversation
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
TatianaBelyukina
requested review from
dlikhomanov and
meanalexrin
as code owners
|
Please export IPython notebook to the .py file and include this .py file into the pull request |
meanalexrin
requested changes
Feb 1, 2021
There was a problem hiding this comment.
Please move you work to the /[username]_code location, as described in readme
https://github.com/rnd4u-org/2021-knu-cairl#development
…ask1_Titanic/main.py
…na_code/task1_Titanic/requirements.txt
…e/task1_Titanic/main.ipynb
…de/task1_Titanic/titanic.csv
meanalexrin
previously approved these changes
Feb 8, 2021
| x_train, y_train, x_test, y_test = load_data() | ||
| model = build_model() | ||
|
|
||
| model.fit(x_train, y_train) |
There was a problem hiding this comment.
Consider using if name == "__main__": to indicate entry point to program
It also may help you in future if you'll ever try to use multiprocessing library
Sign up for free
to join this conversation on GitHub.
Already have an account?
Sign in to comment
Add this suggestion to a batch that can be applied as a single commit.
This suggestion is invalid because no changes were made to the code.
Suggestions cannot be applied while the pull request is closed.
Suggestions cannot be applied while viewing a subset of changes.
Only one suggestion per line can be applied in a batch.
Add this suggestion to a batch that can be applied as a single commit.
Applying suggestions on deleted lines is not supported.
You must change the existing code in this line in order to create a valid suggestion.
Outdated suggestions cannot be applied.
This suggestion has been applied or marked resolved.
Suggestions cannot be applied from pending reviews.
Suggestions cannot be applied on multi-line comments.
Suggestions cannot be applied while the pull request is queued to merge.
Suggestion cannot be applied right now. Please check back later.
Description
First we process the data:
delete this columns ('PassengerId', 'Ticket', 'Name', 'Cabin') because they don't
have any useful information besides column 'Name' from where we get 'Age';
split such columns as "Sex", "Embarked" by values in order to get table with '0' and '1'
"Age", "Fare", "Parch", "SibSp" split by intervals of values;
Training:
tried different models from sklearn. Compared accuracies and chose SVC
with radial basis function that has ~82% accuracy, and 77.5 on kaggle
How has this been tested?