min-max-scaler

There are 0 repository under min-max-scaler topic.

jeremy191 / clustering-based-anomaly-detection
This clustering based anomaly detection project implements unsupervised clustering algorithms on the NSL-KDD and IDS 2017 datasets
nsl-kdd dbscan-algorithm clustering clustering-algorithms lof dataset isolation-forest anaconda kmeans-clustering f1-score min-max-scaler onehot-encoder ids2017 missing-values simple-imputer normalized-mutual-info anomaly-detection score-metrics
Language:Jupyter Notebook 48
shanuhalli / Assignment-Clustering
Perform Clustering (Hierarchical, K Means Clustering and DBSCAN) for the airlines and crime data to obtain optimum number of clusters. Draw the inferences from the clusters obtained.
clustering data-preprocessing dbscan-clustering dendogram dimensionality-reduction elbow-method exploratory-data-analysis hirarchical-clustering k-means-clustering min-max-scaler silhouette-score standard-scaler assignment-07
Language:Jupyter Notebook 3
vaitybharati / P23.-EDA-1
EDA (Exploratory Data Analysis) -1: Loading the Datasets, Data type conversions,Removing duplicate entries, Dropping the column, Renaming the column, Outlier Detection, Missing Values and Imputation (Numerical and Categorical), Scatter plot and Correlation analysis, Transformations, Automatic EDA Methods (Pandas Profiling and Sweetviz).
python eda exploratory-data-analysis data auto-eda pandas-profiling sweetviz scatter-plot correlation-analysis transformations outlier-detection missing-value-imputation numerical-data categorical-data min-max-scaler standard-scaler data-type-conversion
Language:Jupyter Notebook 3
shanuhalli / Assignment-Logistic-Regression
Predicting Customer Response to Telemarketing Campaigns for Term Deposit. Output variable Whether the client has subscribed a term deposit or not.
assignment-06 auc-roc-curve data-preprocessing evaluation-metrics exploratory-data-analysis log-transformation logistic-regression machine-learning min-max-scaler regression sklearn-metrics
Language:Jupyter Notebook 1
shanuhalli / Assignment-PCA
Perform Principal component analysis and perform clustering using first 3 principal component scores both Heirarchial and K Means Clustering and obtain optimum number of clusters and check whether we have obtained same number of clusters with the original data.
data-analysis data-preprocessing dendogram exploratory-data-analysis hirarchical-clustering k-means min-max-scaler pca principal-component-analysis silhouette-method sklearn standard-scaler t-sne assignment-08
Language:Jupyter Notebook 1
Finding-Donors-for-Charity-using-Machine-Learning
sushantdhumak / Finding-Donors-for-Charity-using-Machine-Learning
Machine Learning Nano-degree Project : To help a charity organization identify people most likely to donate to their cause
finding-donors gradient-boosting supervised-learning gridsearchcv data-preprocessing tuning-parameters naive-predictor accuracy f1-score fbeta-score skewed-data data-normalization min-max-scaler confusion-matrix feature-importance feature-selection
Language:Jupyter Notebook 1
ahmetzeki / sorting_reviews_in_Amazon
Evaluating the reviews and sorting them correcly in Amazon
min-max-scaler wilson-lower-bound
Language:Python 0
chinmayeeguru / Lead-Scoring-Logistic-Regression-Model
To predict which customer is most likely to convert
accuracy dummy-variables feature-engineering logistic-regression min-max-scaler one-hot-encoding roc-curve sensitivity specificity
Language:Jupyter Notebook 0
saikrishnabudi / Clustering
Data Science - Clustering Work
clustering-algorithm data-preprocessing dbscan-clustering dbscan-clustering-algorithm dendogram elbow-method exploratory-data-analysis hierarchical-clustering k-means-clustering min-max-scaler silhouette-score standard-scaler
Language:Jupyter Notebook 0
LorenzoRottigni / ML-wines
Machine Learning course of Piero Savastano 6: scaling, MinMaxScaler, KNeighborsClassifier, accuracy_score
accuracy-score k-neighbors machine-learning min-max-scaler scaling
Language:Python
RachitaGurudev / Election-Exit-Poll-Prediction
News channel CNBE wants to analyze recent elections. This survey was conducted on 1525 voters with 9 variables. Model is built to predict which party a voter will vote for on the basis of the given information, to create an exit poll that will help in predicting overall win and seats covered by a particular party.
ada-boost-classifier exploratory-data-analysis gradient-boosting knn-classifier linear-discriminant-analysis logistic-regression min min-max-scaler naive-bayes-classifier
saikrishnabudi / PCA-Principal-Component-Analysis
Data Science - PCA (Principal Component Analysis)
data-preprocessing dendogram exploratory-data-analysis hierarchial-clustering min-max-scaler pca pca-analysis silhouette-score sklearn standard-scaler t-sne
Language:Jupyter Notebook