Titanic: Machine Learning from Disaster (Kaggle Competition)
cynthialo_titanic
cynthialo
Overview
Abstract
# titanic
Titanic: Machine Learning from Disaster (Kaggle Competition)
https://www.kaggle.com/c/titanic
This Kaggle competition asks users to "apply the tools of machine learning to predict which passengers survived the [sinking of the RMS Titanic] tragedy".
Data science involves three main steps:
* Data curation
* Data cleaning and integration
* Data analytics
The models in this repository include:
* Logistic regression: [genderclasslogisticregression.py](genderclasslogisticregression.py)
A simple classification model to get started, using the passengers' socio-economic status, sex, and fare as the features. Here, the model assumptions are:
* Passengers with incomplete data are removed
* No feature scaling is performed
* All features are assumed to be independent
The raw data can be downloaded directly from Kaggle.
Titanic: Machine Learning from Disaster (Kaggle Competition)
https://www.kaggle.com/c/titanic
This Kaggle competition asks users to "apply the tools of machine learning to predict which passengers survived the [sinking of the RMS Titanic] tragedy".
Data science involves three main steps:
* Data curation
* Data cleaning and integration
* Data analytics
The models in this repository include:
* Logistic regression: [genderclasslogisticregression.py](genderclasslogisticregression.py)
A simple classification model to get started, using the passengers' socio-economic status, sex, and fare as the features. Here, the model assumptions are:
* Passengers with incomplete data are removed
* No feature scaling is performed
* All features are assumed to be independent
The raw data can be downloaded directly from Kaggle.
Authoring entity
| Agency Name | Role |
|---|---|
| cynthialo | owner |
Language
English
Methods, software and scripts
Software
| Name | Libraries or packages used |
|---|---|
| Python |
pandas, itertools, sklearn, matplotlib, numpy
|
License
| Name |
|---|
| MIT License |
Metadata production
Producers
| Name | Role |
|---|---|
| GitHub Bot | bot |
Date of Production
01 December 2019