gh-jeremylongshore-claude-code-plugins-plus-plugins-ai-ml-ml-model-trainer/skills/ml-model-trainer/assets/example_dataset.csv

1	# Sample dataset for training a machine learning model.
2	# This dataset contains features and a target variable for demonstration purposes.
3	# You can replace this with your own dataset.
4	# Feature 1: Numerical feature representing age (e.g., of a customer).
5	# Feature 2: Categorical feature representing location (e.g., city).
6	# Feature 3: Binary feature representing whether a customer subscribed (1) or not (0).
7	# Target Variable: Represents the outcome we want to predict (e.g., customer churn).
8	age,location,subscribed,target
9	25,New York,1,0
10	30,Los Angeles,0,1
11	40,Chicago,1,0
12	22,Houston,0,0
13	35,New York,1,1
14	28,Los Angeles,0,0
15	45,Chicago,1,1
16	31,Houston,0,0
17	27,New York,1,0
18	33,Los Angeles,0,1
19	42,Chicago,1,1
20	24,Houston,0,0
21	37,New York,1,0
22	29,Los Angeles,0,0
23	47,Chicago,1,1
24	32,Houston,0,1
25	26,New York,1,0
26	34,Los Angeles,0,1
27	41,Chicago,1,0
28	23,Houston,0,0
29	# Add more rows to create a robust dataset for training.
30	# Consider increasing the number of rows and the diversity of data for better model performance.
31	# Remember to clean and preprocess your data before training.
32	# [ADD_MORE_DATA_HERE]
33	# Example:
34	# 50,San Francisco,1,1
35	# 60,Seattle,0,0
36	# 70,Boston,1,1
37	# 80,Miami,0,0