dmcpbi

Direct marketing campaigns of a Portuguese banking institution (Data-science learning).

Exercises to learning machine learning community.

Dataset: The data is related with direct marketing campaigns of a Portuguese banking institution. The marketing campaigns were based on phone calls. Often, more than one contact to the same client was required, in order to access if the product (bank term deposit) would be ('yes') or not ('no') subscribed.

There are four datasets:

1. bank-additional-full.csv with all examples (41188) and 20 inputs, ordered by date (from May 2008 to November 2010), very close to the data analyzed in [Moro et al., 2014]

2. bank-additional.csv with 10% of the examples (4119), randomly selected from 1), and 20 inputs.

3. bank-full.csv with all examples and 17 inputs, ordered by date (older version of this dataset with less inputs).

4. bank.csv with 10% of the examples and 17 inputs, randomly selected from 3 (older version of this dataset with less inputs). The smallest datasets are provided to test more computationally demanding machine learning algorithms (e.g., SVM).

The classification goal is to predict if the client will subscribe (yes/no) a term deposit (variable y).

Source:
https://archive.ics.uci.edu/ml/datasets.html

Questions:

1. Which profession has the bigger tend to make a loan? Which type?

2. Making a relationship between the number of contacts and campaign success what are the relevant points to be observed?

3. Based on the results of this campaign's accession, what are the average and the maximum number of call you indicate to optimize the accession?

4. Has the result from the previous campaign been relevant to the current campaign?

5. What is the determining factor for the bank to require credit insurance?

6. What are the most prominent characteristics of the clients that has housing loan?

Answers:

First question
Second and third questions
Fourth question
Sixth question

Requirements

python==3.6
pandas==0.23.4
tabulate==0.8.2