Prediction with Neural Networks & SVM
Data-driven prediction with MLP and SVM, compared against classical regression, with proper validation.
Prediction questions with strong nonlinearity and enough data.
A data table with the target variable and variable notes; time-ordered split for series.
Preprocessing, train/test split, error metrics (RMSE/MAE/accuracy), prediction plots and model comparison.
Project file, Do-file / R & Python scripts — 100% reproducible results
Editable Word file, ready for chapter 4 or an ISI/Scopus paper
Path models, causal plots, volatility & Pareto — 300 DPI / SVG
Full statistical interpretation + support until defense or acceptance
Common questions
How much data is enough?
Rule of thumb: at least ~10× inputs; with little data regression is safer.
Neural net instead of regression?
When nonlinearity and accuracy matter more than interpreting coefficients.
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Send your task details in the first message; data review and the quote happen in the same chat.