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        "author": "Boris Yakubchik",
        "author_email": "yboris@yahoo.com",
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        "description": "# Keras History Graph\n\nUses `matplotlib` to generate a simple graph of the history object. Particularly useful with _Jupyter_\n\nIt will show the _accuracy_ and _loss_ for both _training data_ and _validation data_.\nIt will also print the maximum _validation accuracy_ reached during the training.\n\n![Example output](https://user-images.githubusercontent.com/17264277/43170872-5ff85946-8f75-11e8-86e8-d08a0fa79f15.png)\n\n# Installation\n\n`pip install keras-hist-graph`\n\n# Usage\n\nRequires _Keras_\n\n```py\nfrom keras_hist_graph import plot_history\n\nhistory = model.fit(x, y, ...)\n\nplot_history(history)\n```\n\n# Arguments\n\n_plot_history_ now accepts any of these arguments (in any order)\n\n| argument | default | possible | details |\n| -------- | ------- | -------- | ------- |\n| fig_size | (10, 6) | (`float`, `float`) | Indicates _width_ and _height_ of the resulting graph |\n| min_accuracy | 0.5 | `[0, 1)` | Minimum accuracy to graph (often we don't care if acuracy is below 50%) |\n| smooth_factor | 0.75 | `[0, 1]` | Zero to one, inclusive. Smooths out the curves by averaging previous points. Consider makeing smaller if number of epochs is small. |\n| start_epoch | 5 | integer >= 0 | Plot the history starting at this epoch. Useful since the first epochs can have very high loss that makes the later loss hard to analyze visually |\n| xkcd | True | `True` `False` | Whether to render in the _XKCD_ style. You might need to render twice for all properties to update if you change the boolean after using the method before |\n\nExample:\n\n```py\nplot_history(history, fig_size = (11, 8.5), min_accuracy = 0.8, start_epoch = 2, smooth_factor = 0.1)\n```\n\n### Notes\n\n[Why use the XKCD style?](https://www.chrisstucchio.com/blog/2014/why_xkcd_style_graphs_are_important.html)\n\nIt\u2019s a great way to communicate the imprecision of the underlying data!\n\n\n",
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        "name": "keras-hist-graph",
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        "summary": "Graph Keras training history object",
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