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InsightMe is a personal data-driven journal. Capable im importing data, manual tracking, correlating, and prediction. Furthermore it allows to learn about causes by showing the importance of a feature to prediction.
Users can explore data via time-series with a seven-day moving average trend-line:  |
A scatter plot with linear regression and Pearson correlation coefficient to visualize how variables relate to each other:  |
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Mood prediction: Each row represents the contribution of a feature that was selected by L1 regularization. The row contains a red or green bar if the contribution is negative or positive, and the size of the bar indicates the magnitude of the contribution. The black box with whiskers is the mood estimate with its 95% prediction interval:  |
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A visualization explaining how multiple linear regression computes the contribution of a single feature on the final prediction:  |
Another visualization explaining how multiple linear regression computes the contribution of a single feature on the final prediction.  |
The app was built with Flutter and is available on Android and iOS.
Suggest ideas, changes, or new features.
Privacy: All code is open source and all data is stored on your phone, only.