地球资源数据云——数据资源详情
美国警察枪击事件
该数据集《US Police Shootings》主要用于监督学习任务，数据形态以文本为主。 题目说明：Prepared for Visualization 任务类型：文本监督学习。 建议流程：先做文本清洗与分词，再比较 TF - IDF+线性模型 与 预训练语言模型。 评估建议：使用分层切分或交叉验证，优先关注 F1、Recall、AUC 等分类指标。 可用文件：shootings.csv。 Context In the recent killings, a hot topic came into being, "Racism". So, I chose to gather some data to take out some insights and analyze the story around racism in America. I downloaded the raw data from kaggle and prepared it for visualization while correcting values, handling missing content, normalization and categorization Content It contains basic data about people like their name, age, gender and race. Along with it, is the shooting/killing information, like date of event, where it happened? how they were shot? did they attack? Were they holding weapons? Did they show any mental illness? Was the policeman wearing a camera/was the incident recorded? Did the suspect flee? Apart from that, a category column holds type of weapon used by the suspect
摘要概览
该数据集《US Police Shootings》主要用于监督学习任务，数据形态以文本为主。 题目说明：Prepared for Visualization
任务类型：文本监督学习。
建议流程：先做文本清洗与分词，再比较 TF - IDF+线性模型 与 预训练语言模型。
评估建议：使用分层切分或交叉验证，优先关注 F1、Recall、AUC 等分类指标。
可用文件：shootings.csv。
Context
In the recent killings, a hot topic came into being, "Racism". So, I chose to gather some data to take out some insights and analyze the story around racism in America. I downloaded the raw data from kaggle and prepared it for visualization while correcting values, handling missing content, normalization and categorization
Content
It contains basic data about people like their name, age, gender and race. Along with it, is the shooting/killing information, like date of event, where it happened? how they were shot? did they attack? Were they holding weapons? Did they show any mental illness? Was the policeman wearing a camera/was the incident recorded? Did the suspect flee?
Apart from that, a category column holds type of weapon used by the suspect