代写DSC3011语言编程、代写Java，c/c++程序设计、Python语言编程代做

日期：2020-10-19 11:01

DSC3011 Assignment 1: Kaggle InClass Competition

Goal

The goal of assignment 1 is to practice data preprocessing and classification through a

Kaggle InClass Competition. You are expected to understand how Kaggle works and

how you can improve your classification model’s performance.

Task

You are provided with a classification dataset and your task is to build a series of

models with the goal of improving the performance. You can use any data

preprocessing technique and classification method.

Data description

A detailed description is available at

https://archive.ics.uci.edu/ml/datasets/Heart+Disease

The dataset used in the assignment 1 is a slightly modified version with 13 features and

1 categorical target variable. The goal is to use the 13 features and classify each

instance into one of the TWO categories.

How

1) Go to https://www.kaggle.com/t/10130a66f8084a9497ddaf4d74aa172c and

create an account if you don’t have.

2) Go to Data tab and download data files.

? X_train.csv: 233 samples, 13 features (Id should not be counted as a

feature)

? y_train.csv: 233 samples, 1 target (1 or 0, each number represents a

category)

? X_test.csv: 70 samples, 13 features (the dataset you test your model)

? sample_submission.csv: This is a sample submission file and when you

submit your classification result for X_test, your final submission file should

have the same format. It is a csv file with two columns Id and target. Because

it is a sample submission file, it has only 10 samples. The final submission file

should have 70 samples (the same as X_test) with two columns Id and

target. Id column in your submission file is from X_test, and target column

should include your precited results (i.e., 0 or 1). After you do the prediction,

you should generate an output file that has the same format with

sample_sbmission.csv and submit it to the Kaggle. The file name can be

arbitrary.

3) After submitting the result file. you will be able to see the score. The evaluation

method is simple classification accuracy.

4) Try to improve the score by testing different preprocessing and classification

methods. You are allowed to submit up to 20 times a day.

Deliverable

One-page short summary on

? Your Kaggle account

? How many submissions have you tried to improve the performance?

? What methods have you tried?

? Did the methods improve the performance? Why or Why not?

? Please explain your best solution with the highest score (e.g., what classification

method + how you preprocessed the data)

? What have you learned from the competition?

IMPORTANT

1) You don’t need to use your real name for the Kaggle account because the goal of

the competition is to compete with yourselves, not with your peers.

2) The assignment will not be graded based on the Kaggle score. The assignment

will be evaluated based on your one-page summary. Please write it carefully so

that I can evaluate your efforts.

3) As I already disclosed the data source, you can find the correct answers easily

on the web. Any attempts to artificially make submission files using correct

answers will be regarded as PLAGIARISM.

4) If you have questions on reading the dataset and generating the submission files

you can ask me or your peers. However, solutions should be your own.