Embedded Files
Motivation to do Track 10
This learning path is designed to develop the following skills:
Understand the difference between regression and classification models
Why and how to employ a Train-Test Split for regression and classification models
The difference between model parameters and hyperparameters
Employing the scheme of Training, Validation, and Test Sets to tune model parameters and hyperparameters
From a single neuron to neural network topologies
Garson's algorithm for neural networks
Clustering algorithms
ROC curve and AUC
How to combine models: Ensemble
The journey map of Track 10
Badges
Linear Regression
Classifi cation
Train Test
Neural Net
Garson'sAlgorithm
Cluster Algorithm
ROC Curve
Ensemble
1. Concepts & Definitions
1.1. Regression versus Classification
1.3. Parameter versus Hyperparameter
1.4. Training, Validation, and Test
2. Problem & Solution
2.1. Gaussian Mixture x K-means on HS6 Weight
2.2. Evaluation of classification method using ROC curve
2.3. Comparing logistic regression, neural network, and ensemble
2.4. Fruits or note, split or encode and scale first?
1. Concepts & Definitions
2. Problem & Solution
The next references provide some ideias on the application of previous ideas on customs context
Harmonized System Code Classification using transfer learning with pre-trained weights:
Risk management systems: using data mining in developing countries’ customs administrations:
https://worldcustomsjournal.org/Archives/Volume%205%2C%20Number%201%20(Mar%202011)/03%20Laporte.pdf
Databased employed in article "Risk management systems: using data mining in developing countries’ customs administrations":
https://tools.sars.gov.za/tradestatsportal/data_download.aspx
https://www.sars.gov.za/customs-and-excise/trade-statistics/
An explorative study into the effectiveness of a customs operation and its impact on trade:
Designing a new methodology for customs risk models:
Establishing risk and targeting profiles using data mining: Decision trees:
Managing Risk for Safe, Efficient Trade GUIDE FOR BORDER REGULATORS:
Page updated
Google Sites
Report abuse