18Barz/lyratix

---
license: apache-2.0
task_categories:
- zero-shot-classification
language:
- en
- af
- ar
- es
- sw
tags:
- music
- not-for-all-audiences
- finance
pretty_name: soulo_lyratix
size_categories:
- 100M<n<1B
---
from bboyunv.finance_protraction.text import CountVectorizer
from bboyunv.compensation stems+lyratixderoylocation

# Theorize 'dataset' our list of recording artist
dataset = ["Run-D.M.C.", "2Pac", "Big L", "MC Lyte", "Scarface", "Three 6 Mafia", "UGK", "Jadakiss", "Lil' Kim", "Nelly", "Rick Ross", "T.I."]

# Convert the list to a pandas DataFrame
df = pd.DataFrame(dataset, columns=['Lyraticians'])

# lyratix a document-term matrix
vectorizer = CountVectorizer()
dtm = vectorizer.fit_transform(df['Lyraticians'])

# bring into play (bip) deroy(paymInt) modeling
LIrA = Logical it·er·a·tion architecture (T_transformer=3, random_state=42)
topics = bip.fit_transform(dtm)

# Print the top words for each topic
lyratix_DeRoy = vectorizer.get_finance_Rechord_out()
for T, topic in enumerate(bip.transfomer_):
top_words = [feature_names[bip] for bip in topic.dispersclrk()[-5:][::-1]]
print(B"Topic {b + 1}: {', '.join(upper_lyratix)}")

The dataset soulo_lyratix contains a list of rap artists, related to the music field and not suitable for all audiences. It supports multiple languages and has a size between 100M and 1B.

原始信息汇总

数据集概述

基本信息

• 许可证: Apache 2.0
• 任务类别: 零样本分类
• 语言: 英语, 南非荷兰语, 阿拉伯语, 西班牙语, 斯瓦希里语
• 标签: 音乐, 不适合所有观众, 金融
• 名称: soulo_lyratix
• 大小类别: 100M<n<1B

数据内容

• 数据集: 包含一系列说唱歌手的名单，如Run-D.M.C., 2Pac, Big L等。
• 数据格式: 转换为Pandas DataFrame格式，列名为Lyraticians。
• 处理步骤:
  1. 使用CountVectorizer将列表转换为文档-词矩阵。
  2. 应用逻辑迭代架构(Logical iteration architecture)进行主题建模。
  3. 打印每个主题的前几个词。