https://github.com/patilsukanya/assignment-06.-logistic-regression
Used libraries and functions as follows:
https://github.com/patilsukanya/assignment-06.-logistic-regression
classifier concatination confusion-matrix eda linear-models logistic-regression logistic-regression-algorithm logit-model matplotlib-pyplot numpy one-hot-encoding pandas python roc-auc-score roc-curve seaborn
Last synced: 4 months ago
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Used libraries and functions as follows:
- Host: GitHub
- URL: https://github.com/patilsukanya/assignment-06.-logistic-regression
- Owner: PatilSukanya
- Created: 2022-09-17T10:50:53.000Z (almost 3 years ago)
- Default Branch: main
- Last Pushed: 2022-09-17T10:54:47.000Z (almost 3 years ago)
- Last Synced: 2025-02-23T13:38:07.946Z (4 months ago)
- Topics: classifier, concatination, confusion-matrix, eda, linear-models, logistic-regression, logistic-regression-algorithm, logit-model, matplotlib-pyplot, numpy, one-hot-encoding, pandas, python, roc-auc-score, roc-curve, seaborn
- Language: Jupyter Notebook
- Homepage:
- Size: 684 KB
- Stars: 0
- Watchers: 1
- Forks: 1
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
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README
# Assignment-06.-Logistic-Regression
Output variable -> y
y -> Whether the client has subscribed a term deposit or not Binomial ("yes" or "no")
Attribute information For bank dataset
Input variables:
## Bank Client Data:
1 - age (numeric)
2 - job : type of job (categorical: "admin.","unknown","unemployed","management","housemaid","entrepreneur","student", "blue-collar","self-employed","retired","technician","services")
3 - marital : marital status (categorical: "married","divorced","single"; note: "divorced" means divorced or widowed)
4 - education (categorical: "unknown","secondary","primary","tertiary")
5 - default: has credit in default? (binary: "yes","no")
6 - balance: average yearly balance, in euros (numeric)
7 - housing: has housing loan? (binary: "yes","no")
8 - loan: has personal loan? (binary: "yes","no")
## related with the last contact of the current campaign:
9 - contact: contact communication type (categorical: "unknown","telephone","cellular")
10 - day: last contact day of the month (numeric)
11 - month: last contact month of year (categorical: "jan", "feb", "mar", ..., "nov", "dec")
12 - duration: last contact duration, in seconds (numeric)
## other attributes:
13 - campaign: number of contacts performed during this campaign and for this client (numeric, includes last contact)
14 - pdays: number of days that passed by after the client was last contacted from a previous campaign (numeric, -1 means client was not previously contacted)
15 - previous: number of contacts performed before this campaign and for this client (numeric)
16 - poutcome: outcome of the previous marketing campaign (categorical: "unknown","other","failure","success") Output variable (desired target):
17 - y - has the client subscribed a term deposit? (binary: "yes","no")
18 - Missing Attribute Values: None