Definition, implementation and pros and cons of decision tree models. What is a decision tree? A decision tree is a simple model for 'supervised' classification/regression. Each in
Category
Machine Learning
9 articles in this topic.
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Some types of plots and how can they be helpful for machine learning tasks, such as feature selection. Data exploration During data exploration, we can use plots below to find more
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Including methods implemented during EDA and data lacking. Lack of Training Data (数据短缺) --- Data Augmentation (数据增强) Expand an input dataset by slightly changing the existing (orig
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Different data types in ML. Interval Data This is numerical data which has proper order and the exact zero . Temperature, time, credit score, pH... (zero value exists) Ratio Data T
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Mathematics in machine learning IQR (Interquartile Range) IQR describes the distance between the 1st quartile and the 3rd quartile. It is a method to detect outliers in dataset. ou
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Evaluate a model and decide what to do next. Model Evaluation Train Test Split Split the dataset to: 70% for training and 30% for testing. --- Train/test Procedure for Linear Regre
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Notions about gradient descent. Optimizing Learning Algorithm --- Feature Engineering (特征工程) Use intuition to create new features, by combining and transforming the original ones.
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logistic regression model Logistic Regression --- Compared with linear regression, logistic regression is used to solve questions which only have limited possible answers. For exam
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linear regression model 线性回归模型(Linear Regression) --- 线性回归模型可以根据一些特征值(feature x)数据, 计算一个可能的结果(预测), 这个结果是无限多个数中的一个. 例如根据房屋个数, 房屋面积, 花园面积和房屋建成年份等特征值进行房价预测等. In a word, linear regress