Here I will apply following algorithms on Donor Choose Dataset

• Decision Tree
• XGBoost

Link to Kaggle Dataset

DonorsChoose

DonorsChoose is a United States-based nonprofit organization that allows individuals to donate directly to public school classroom projects. The organization has been given Charity Navigator's highest rating every year since 2005.[4] In January 2018, they announced that 1 million projects had been funded. In 80% of public schools in the United States, at least one project has been requested on DonorsChoose. Schools from wealthy areas are more likely to make technology requests, while schools from less affluent areas are more likely to request basic supplies.[6] It has been noted that repeat donors on DonorsChoose typically donate to projects they have no prior relationship with, and most often fund projects serving financially challenged students.

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About the DonorsChoose Data Set

The train.csv data set provided by DonorsChoose contains the following features:

Feature	Description
project_id	A unique identifier for the proposed project. Example: p036502
project_title	Title of the project. Examples: Art Will Make You Happy! First Grade Fun
project_grade_category	Grade level of students for which the project is targeted. One of the following enumerated values: Grades PreK-2 Grades 3-5 Grades 6-8 Grades 9-12
project_subject_categories	One or more (comma-separated) subject categories for the project from the following enumerated list of values: Applied Learning Care & Hunger Health & Sports History & Civics Literacy & Language Math & Science Music & The Arts Special Needs Warmth Examples: Music & The Arts Literacy & Language, Math & Science
school_state	State where school is located (Two-letter U.S. postal code). Example: WY
project_subject_subcategories	One or more (comma-separated) subject subcategories for the project. Examples: Literacy Literature & Writing, Social Sciences
project_resource_summary	An explanation of the resources needed for the project. Example: My students need hands on literacy materials to manage sensory needs!</code
project_essay_1	First application essay*
project_essay_2	Second application essay*
project_essay_3	Third application essay*
project_essay_4	Fourth application essay*
project_submitted_datetime	Datetime when project application was submitted. Example: 2016-04-28 12:43:56.245
teacher_id	A unique identifier for the teacher of the proposed project. Example: bdf8baa8fedef6bfeec7ae4ff1c15c56
teacher_prefix	Teacher's title. One of the following enumerated values: nan Dr. Mr. Mrs. Ms. Teacher.
teacher_number_of_previously_posted_projects	Number of project applications previously submitted by the same teacher. Example: 2

^* See the section Notes on the Essay Data for more details about these features.

Additionally, the resources.csv data set provides more data about the resources required for each project. Each line in this file represents a resource required by a project:

Feature	Description
id	A project_id value from the train.csv file. Example: p036502
description	Desciption of the resource. Example: Tenor Saxophone Reeds, Box of 25
quantity	Quantity of the resource required. Example: 3
price	Price of the resource required. Example: 9.95

Note: Many projects require multiple resources. The id value corresponds to a project_id in train.csv, so you use it as a key to retrieve all resources needed for a project:

The data set contains the following label (the value you will attempt to predict):

Label	Description
project_is_approved	A binary flag indicating whether DonorsChoose approved the project. A value of 0 indicates the project was not approved, and a value of 1 indicates the project was approved.