TY - GEN
T1 - Support vector mind map of wine speak
AU - Flanagan, Brendan
AU - Hirokawa, Sachio
N1 - Funding Information:
This work was supported by JSPS KAKENHI Grant Number 15J04830.
Publisher Copyright:
© Springer International Publishing Switzerland 2016.
PY - 2016
Y1 - 2016
N2 - Models created by blackbox machine learning techniques such as SVM can be difficult to interpret. It is because these methods do not offer a clear explanation of how classifications are derived that is easy for humans to understand. Other machine learning techniques, such as: decision trees, produce models that are intuitive for humans to interpret. However, there are often cases where an SVM model will out preform a more intuitive model, making interpretation of SVM trained models an important problem. In this paper, we propose a method of visualizing linear SVM models for text classification by analyzing the relation of features in the support vectors. An example of this method is shown in a case study into the interpretation of a model trained on wine tasting notes.
AB - Models created by blackbox machine learning techniques such as SVM can be difficult to interpret. It is because these methods do not offer a clear explanation of how classifications are derived that is easy for humans to understand. Other machine learning techniques, such as: decision trees, produce models that are intuitive for humans to interpret. However, there are often cases where an SVM model will out preform a more intuitive model, making interpretation of SVM trained models an important problem. In this paper, we propose a method of visualizing linear SVM models for text classification by analyzing the relation of features in the support vectors. An example of this method is shown in a case study into the interpretation of a model trained on wine tasting notes.
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U2 - 10.1007/978-3-319-40349-6_13
DO - 10.1007/978-3-319-40349-6_13
M3 - Conference contribution
AN - SCOPUS:84978785910
SN - 9783319403489
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 127
EP - 135
BT - Human Interface and the Management of Information
A2 - Yamamoto, Sakae
PB - Springer Verlag
T2 - 18th International Conference on Human-Computer Interaction, HCI International 2016
Y2 - 17 July 2016 through 22 July 2016
ER -