roc-auc-score

There are 0 repository under roc-auc-score topic.

Lakshmipriya-S / Jobathon-Analytics-Vidhya
Lead generation for credit card
prediction analytics-vidhya-competition credit-card jobathon bank roc-auc-score leads feature-engineering revenue fold consists gradient
Language:Jupyter Notebook 5
pajaskowiak / clusterConfusion
Clustering validation with ROC Curves
auc-score clustering clustering-algorithm clustering-analysis clustering-evaluation clustering-validation hierarchical-clustering k-means k-means-clustering roc-analysis roc-auc roc-auc-curve roc-auc-score roc-curve roc-curves roc-plot
Language:R 5
rochitasundar / TwitterSentimentAnalysis-BigDataProject
Scrapped tweets using twitter API (for keyword ‘Netflix’) on an AWS EC2 instance, ingested data into S3 via kinesis firehose. Used Spark ML on databricks to build a pipeline for sentiment classification model and Athena & QuickSight to build a dashboard
accuracy-metrics aws-athena aws-ec2 aws-kinesis-firehose aws-quicksight aws-s3 count-vectorizer databricks-notebooks pyspark python3 roc-auc-score tf-idf-vectorizer twitter-api twitter-sentiment-analysis multiclass-evaluator
Language:Jupyter Notebook 4
AV-Jobathon-May-21
developedbysm / AV-Jobathon-May-21
credit card lead prediction
credit-card roc-auc-score prediction bank leads analyticsvidhya 2021 data-science dataanalysis feature-engineering gradient revenue fold consists analytics-vidhya-competition
Language:Jupyter Notebook 3
Safaa-p / Disease-classification-Plant-Village-dataset
Develop and train image classification models using advanced deep learning techniques to identify diseases specific to apples.
classification computer-vision deep-learning desease grad-cam grad-cam-visualization imagehash inceptionv3 mobilenet normalization resnet-50 roc-auc-curve roc-auc-score tensorflow tf-keras-vis
Language:Jupyter Notebook 2
vaitybharati / Assignment-06-Logistic-Regression
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") 8. Missing Attribute Values: None
python logistic-regression pandas numpy matplotlib-pyplot seaborn linear-model confusion-matrix roc-curve roc-auc-score eda one-hot-encoding concatenation classifier logit-model logistic-regression-algorithm
Language:Jupyter Notebook 2
Harmanveer2546 / Wafer-Fault-Detection
The goal is to eliminate manual work in identifying faulty wafers. Opening and handling suspected wafers disrupts the entire process. False negatives result in wasted time, manpower, and costs.
machine-learning numpy pandas python random-forest roc-auc-curve roc-auc-score sklearn-library svc xgboost
Language:Jupyter Notebook 1
GunturWibawa / BetaBankChurnAnalysis
Beta Bank is losing customers monthly. Employees want to focus on client retention. As a Data Scientist, I created a model to predict the chance of a customer leaving, based on past behavior and contract terminations.
bank decisiontreeclassifier f1-score matplotlib-pyplot mean-absolute-error mean-squared-error numpy pandas python3 r2-score randomforrestclassifier roc-auc-score scipy-stats seaborn sklearn
Language:Jupyter Notebook 0
JustAbhishek / Credit-Card-Lead-Prediction
It is a Hackathon problem statement solution, which is arranged by Analytics Vidhya.
machine-learning-algorithms credit-risk python jobathon roc-auc-score
Language:Jupyter Notebook 0
PatilSukanya / Assignment-06.-Logistic-Regression
Used libraries and functions as follows:
classifier 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 concatination
Language:Jupyter Notebook 0
tpurcell0122github / INNHotels
A Portuguese hotel group seeks to understand reasons for its excessive cancellation rates.
confusion-matrix decision-trees featureimportances logistic-regression multicollinearity precision-recall-curve pruning roc-auc-curve roc-auc-score cost-complexity-pruning visualization
0
utkarsh-21st / dimensionality-reduction-using-auto-encoder
Perform Dimensionality Reduction using AutoEncoder.
xgboost-classification-model low-dimensional-features roc-auc-score autoencoder keras
Language:Jupyter Notebook 0
harmanveer-2546 / Wafer-Fault-Detection
The goal is to eliminate manual work in identifying faulty wafers. Opening and handling suspected wafers disrupts the entire process. False negatives result in wasted time, manpower, and costs.
machine-learning matplotlib numpy pandas python random-forest roc-auc-curve roc-auc-score seaborn sklearn svc xgboost clustering data-transformation feature-selection
Language:Jupyter Notebook
tacotuesday / develop_zscore_and_baseline_results
ROC, AUC, and Z-score functions for anomaly detection
anomaly-detection roc-auc-score z-score
Language:Python
waannuullll / telco-churn-prediction
Increased the ROC AUC score by 2.14% of predicting the churn of users in telecommunication company using hypertuning parameter and feature engineering.
machine-learning data-science statistical-analysis roc-auc-score logistic-regression support-vector-machines k-nearest-neighbours
Language:Jupyter Notebook

roc-auc-score

Lakshmipriya-S / Jobathon-Analytics-Vidhya

pajaskowiak / clusterConfusion

rochitasundar / TwitterSentimentAnalysis-BigDataProject

developedbysm / AV-Jobathon-May-21

Safaa-p / Disease-classification-Plant-Village-dataset

vaitybharati / Assignment-06-Logistic-Regression

Harmanveer2546 / Wafer-Fault-Detection

GunturWibawa / BetaBankChurnAnalysis

JustAbhishek / Credit-Card-Lead-Prediction

PatilSukanya / Assignment-06.-Logistic-Regression

tpurcell0122github / INNHotels

utkarsh-21st / dimensionality-reduction-using-auto-encoder

harmanveer-2546 / Wafer-Fault-Detection

tacotuesday / develop_zscore_and_baseline_results

waannuullll / telco-churn-prediction