04-29-2017, 02:33 AM
SYLLABUS:-
UNIT- I
Overview of R or Octave statistical package, Data Pre-processing, Data Scales, Similarity and Dissimilarity measures, sampling and quantization of data, filtering, Data transformation and merging, Data visualization, PCA, Correlation, Chi-Square test. Illustration of These techniques through R, or Octave.
UNIT- II
Regression Analysis, linear, generalized, regularized regression, Cross-validation, Training and Testing data set, Overview of nonlinear regression, Overview of Ridge regression, Latent variables, Structure Equation modelling. Illustration of These techniques through R, or Octave.
UNIT- III
Forecasting, time series data analysis, Stationarity, Seasonality, recurrent models, autoregressive models. Illustration of These techniques through R, or Octave.
UNIT- IV
Classification, Linear discriminant analysis, overview of support vector machine, Decision trees, Clustering, Clustering techniques. Illustration of These techniques through R, or Octave
UNIT- I
Overview of R or Octave statistical package, Data Pre-processing, Data Scales, Similarity and Dissimilarity measures, sampling and quantization of data, filtering, Data transformation and merging, Data visualization, PCA, Correlation, Chi-Square test. Illustration of These techniques through R, or Octave.
UNIT- II
Regression Analysis, linear, generalized, regularized regression, Cross-validation, Training and Testing data set, Overview of nonlinear regression, Overview of Ridge regression, Latent variables, Structure Equation modelling. Illustration of These techniques through R, or Octave.
UNIT- III
Forecasting, time series data analysis, Stationarity, Seasonality, recurrent models, autoregressive models. Illustration of These techniques through R, or Octave.
UNIT- IV
Classification, Linear discriminant analysis, overview of support vector machine, Decision trees, Clustering, Clustering techniques. Illustration of These techniques through R, or Octave