Kolmogorov-Arnold Networkのマーケティング解析への応用可能性の検討
従来的な深層学習手法との理論的比較と実データによる購買予測への応用
DOI:
https://doi.org/10.51094/jxiv.893キーワード:
機械学習、 深層学習、 Kolmogorov-Arnold Network、 マーケティング、 購買予測抄録
近年、深層学習をはじめとした機械学習手法は急速な進化を続けている。例としてメディアデータの生成が可能な拡散モデルや、自然なコミュニケーションが可能な大規模言語モデルが登場しており、幅広い分野において大きな影響を及ぼしている。また、従来の深層学習とは異なるアーキテクチャーをもつモデルとして、Kolmogorov--Arnold Network (KAN)が注目され、それをベースとしたモデルが立て続けに提案されている。しかしながら、社会科学における応用は必ずしも進んでいるとはいえず、その応用可能性は不明瞭である。そこで本研究では、まずここまでの深層学習の発展について網羅的に俯瞰した上で、KANを使用した将来購買の予測を行うとともに、モデル探索を通じて各パラメーターの効果について検証する。また、KANの有用性の一つである活性化関数の可視化を通じて、マーケティング分析への応用可能性を検討する。
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投稿日時: 2024-09-16 09:33:22 UTC
公開日時: 2024-09-19 00:52:13 UTC
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