User:Malymichal/Books/Data Science
 | The Wikimedia Foundation's book rendering service has been withdrawn. Please upload your Wikipedia book to one of the external rendering services. |
 | You can still create and edit a book design using the Book Creator and upload it to an external rendering service:
|
| This user book is a user-generated collection of Wikipedia articles that can be easily saved, rendered electronically, and ordered as a printed book. If you are the creator of this book and need help, see Help:Books (general tips) and WikiProject Wikipedia-Books (questions and assistance). Edit this book: Book Creator · Wikitext Order a printed copy from: PediaPress [ About ] [ Advanced ] [ FAQ ] [ Feedback ] [ Help ] [ WikiProject ] [ Recent Changes ] | ||||||||
Data Science
[edit]- Statistics
- Accuracy and precision
- Aggregate function
- Analysis of covariance
- Analysis of variance
- Analytics
- Anscombe's quartet
- Artificial neural network
- Base rate fallacy
- Bias (statistics)
- Bias–variance tradeoff
- Big data
- Boole's inequality
- Business analytics
- Business intelligence
- Business reporting
- Canonical correlation
- Cherry picking
- Classifier chains
- Cluster analysis
- Configural frequency analysis
- Confusion matrix
- Contingency table
- Convex optimization
- Correlation and dependence
- Cross-validation (statistics)
- Data
- Data analysis
- Data dredging
- Data mining
- Data model
- Data quality
- Data science
- Data set
- Data visualization
- Data warehouse
- Decision boundary
- Dependent and independent variables
- Descriptive statistics
- Design matrix
- Dimensionality reduction
- Distributed computing
- Eigenvalues and eigenvectors
- Exploratory data analysis
- False discovery rate
- False positives and false negatives
- False precision
- Feature (machine learning)
- Fisher kernel
- Forecasting
- Gaussian process
- Geostatistics
- Graph kernel
- Hierarchical database model
- Hyperparameter optimization
- Independence (probability theory)
- Influential observation
- Information extraction
- Instance-based learning
- Inverse distance weighting
- Jackknife variance estimates for random forest
- Kernel method
- Kernel methods for vector output
- Kernel perceptron
- Kernel smoother
- Kriging
- Latent class model
- Law of total covariance
- Law of total variance
- Linear classifier
- Linear discriminant analysis
- Linear model
- Linear regression
- Logic learning machine
- Logistic regression
- Machine learning
- Mathematics of artificial neural networks
- Multidimensional analysis
- Navigational database
- Normal distribution
- Observational error
- OLAP cube
- Online analytical processing
- Online transaction processing
- Outlier
- Overfitting
- Pattern recognition
- Perceptron
- Positive-definite kernel
- Precision (statistics)
- Precision and recall
- Predictive analytics
- Predictive modelling
- Principal component analysis
- Probability distribution
- Propagation of uncertainty
- Rademacher complexity
- Radial basis function kernel
- Randomness
- Ranking
- Regression analysis
- Regression validation
- Repeatability
- Representer theorem
- Reproducibility
- Robust statistics
- Sample size determination
- Sensitivity and specificity
- Sensor
- Spectral clustering
- Statistical classification
- Statistical dispersion
- Statistical hypothesis testing
- Statistical inference
- Statistical learning theory
- Statistical model
- Statistical population
- Statistical significance
- Statistical theory
- Statistics
- String kernel
- Structured data analysis (statistics)
- Supervised learning
- Support-vector machine
- Testing hypotheses suggested by the data
- Text mining
- Unstructured data
- Unsupervised learning
- Algorithms and Software
- AdaBoost
- Apache Flink
- Apache Hadoop
- Apache Spark
- Elastic net regularization
- K-nearest neighbors algorithm
- Kaggle
- Lasso (statistics)
- LIBSVM
- LogitBoost
- MapReduce
- R (programming language)
- Scikit-learn
- Winnow (algorithm)
- XGBoost
- Advanced concepts
- Adaptive filter
- Tikhonov regularization