evaluation on sentiment dataset
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								Project/simple_approach/Evaluation_sentiment_dataset.ipynb
									
									
									
									
									
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								Project/simple_approach/Evaluation_sentiment_dataset.ipynb
									
									
									
									
									
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							| @ -68,7 +68,7 @@ def sentiment_score(s): | ||||
|     #(pos, neg, neu)^T | ||||
|     return s[0] - s[1] | ||||
|  | ||||
| def plot_sentiment_space(predicted_sentiment_vectors, top_sentiments, top_emojis): | ||||
| def plot_sentiment_space(predicted_sentiment_vectors, top_sentiments, top_emojis, style='bo'): | ||||
|     # sentiment score axis | ||||
|     top_X = np.array([sentiment_score(x) for x in top_sentiments]) | ||||
|     pred_X = np.array([sentiment_score(x) for x in predicted_sentiment_vectors]) | ||||
| @ -85,7 +85,7 @@ def plot_sentiment_space(predicted_sentiment_vectors, top_sentiments, top_emojis | ||||
|     plt.ylim([0,1]) | ||||
|     for i in range(len(top_X)): | ||||
|         plt.text(top_X[i], top_Y[i], top_emojis[i]) | ||||
|     plt.plot(pred_X, pred_Y, 'bo') | ||||
|     plt.plot(pred_X, pred_Y, style) | ||||
|     plt.savefig("val-error_sentiment-plot" + str(datetime.datetime.now()) +  ".png", bbox_inches='tight') | ||||
|  | ||||
|     # sentiment score axis | ||||
| @ -104,7 +104,7 @@ def plot_sentiment_space(predicted_sentiment_vectors, top_sentiments, top_emojis | ||||
|     plt.ylim([0,1]) | ||||
|     for i in range(len(top_X)): | ||||
|         plt.text(top_X[i], top_Y[i], top_emojis[i]) | ||||
|     plt.plot(pred_X, pred_Y, 'bo') | ||||
|     plt.plot(pred_X, pred_Y, style) | ||||
|     plt.savefig("val-error_positive-negative-plot" + str(datetime.datetime.now()) + ".png", bbox_inches='tight') | ||||
|     plt.show() | ||||
|  | ||||
|  | ||||
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