【数据科学】常用数据科学缩写

• ANOVA : Analysis of Variance
• AUC : Area Under the Curve
  
  also known as AUROC: Area Under Receiver Operating Characteristic
• CV: Cross Validation
• CNN : Convolutional Neural Network
• DNN: Deep Neural Network or Deconvolutional Neural Network
• EDA: Exploratory Data Analysis
• GBM: Gradient Boosting Machine
• GLM: Generalized Linear Model
• GRU: Gated Recurrent Unit
• HMM : Hidden Marcov Model
• ICA: Independent Component Analysis
• kNN: k-Nearest Neighbors
• LB: LeaderBoard
• LDA: Latent Dirichlet Allocation or Linear Discriminant Analysis
• LLE : Locally Linear Embedding
• LOOCV : Leave-One-Out cross-validation
• LpO CV : Leave-p-out cross-validation
• LSA/LSI: Latent Semantic Allocation/Indexing
• LSTM: Long Short Term Memory
• MAPE: Mean Absolute Percentage Error
• MCMC : Markov Chain Monte Carlo
• MDS : Multi-Dimensional Scaling
• MSE: Mean Squared Error
• NLDR: Non-Linear Dimensionality Reduction
• NLP : Natural Language Processing
• NMF: Non-Negative Matrix Factorization
• OOF: Out Of Fold
• PCA: Principal Component Analysis
• pLSA: Probabilistic Latent Semantic Allocation
• R2 : R-squared
• RF: Random Forest
• RFE: Recursive Feature Elimination
• RMSLE : Root Mean Squared Logarithmic Error
• RNN: Recurrent Neural Network
• ROC : Receiver Operating Characteristic
• SMOTE: Synthetic Minority Over-sampling Technique
• SVM: Support Vector Machine
• tf-idf: term frequency, inverse document frequency
• t-SNE: t-Distributed Stochastic Neighbor Embedding
• LB stands for LeaderBoard;
• CV stands for Cross Validation https://en.wikipedia.org/wiki/Cross-validation_(statistics);
• DNN stands for Deep Neural Network;
• CNN stands for Convolutional Neural Network;
• RNN stands for Recurrent Neural Network;
• SVM stands for Support Vector Machine.
• SMOTE: Synthetic Minority Over-sampling Technique
• LSA/LSI: Latent Semantic Allocation/Indexing
• pLSA: Probabilistic Latent Semantic Allocation
• NMF: Non-Negative Matrix Factorization
• kNN: k-Nearest Neighbors
• RFE: Recursive Feature Elimination
• RF: Random Forest
• ICA: Independent Component Analysis
• PCA: Principal Component Analysis

• LOOV : Leave-One-Out cross-validation

• LKOV : Leave-k-Out cross-validation

• RMSLE : Root Mean Squared Logarithmic Error

• R2 : R-squared (regression metrics)

• ROC : Receiver Operating Characteristic

• AUC : Area Under the Curve (ROC curve)

• MDS : Multidimensional Scaling

• LLE : Locally Linear Embedding

• HMM : Hidden Marcov Model

• MCMC : Markov chain Monte Carlo

• ANOVA : Analysis of Variance

• NLP : Natural Language Processing

原文：https://www.kaggle.com/getting-started/38187