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some improvements

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This commit is contained in:
Jonas Weinz 2018-07-23 20:11:24 +02:00
parent 14f5166fda
commit 4f1f004fd8
3 changed files with 466 additions and 47 deletions
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20
Project/Tools/emoji_plotting.ipynb
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@ -181,24 +181,6 @@
"source": [ "source": [
"plot_emoji_list(sentiment_vectors=edist.list_sentiment_vectors, unicode_repr=edist.list_emojis, title=\"Full Emoji space\")" "plot_emoji_list(sentiment_vectors=edist.list_sentiment_vectors, unicode_repr=edist.list_emojis, title=\"Full Emoji space\")"
] ]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": []
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": []
} }
], ],
"metadata": { "metadata": {
@ -217,7 +199,7 @@
"name": "python", "name": "python",
"nbconvert_exporter": "python", "nbconvert_exporter": "python",
"pygments_lexer": "ipython3", "pygments_lexer": "ipython3",
"version": "3.6.3" "version": "3.6.5"
} }
}, },
"nbformat": 4, "nbformat": 4,

485
Project/simple_approach/Evaluation_sentiment_dataset.ipynb
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File diff suppressed because one or more lines are too long

8
Project/simple_approach/simple_twitter_learning.py
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@ -68,7 +68,7 @@ def sentiment_score(s):
#(pos, neg, neu)^T #(pos, neg, neu)^T
return s[0] - s[1] return s[0] - s[1]
def plot_sentiment_space(predicted_sentiment_vectors, top_sentiments, top_emojis, style='bo'): def plot_sentiment_space(predicted_sentiment_vectors, top_sentiments, top_emojis, style='bo', additional_patches = None):
# sentiment score axis # sentiment score axis
top_X = np.array([sentiment_score(x) for x in top_sentiments]) 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]) pred_X = np.array([sentiment_score(x) for x in predicted_sentiment_vectors])
@ -86,6 +86,9 @@ def plot_sentiment_space(predicted_sentiment_vectors, top_sentiments, top_emojis
for i in range(len(top_X)): for i in range(len(top_X)):
plt.text(top_X[i], top_Y[i], top_emojis[i]) plt.text(top_X[i], top_Y[i], top_emojis[i])
plt.plot(pred_X, pred_Y, style) plt.plot(pred_X, pred_Y, style)
for p_tuple in additional_patches:
ax_1.add_artist(p_tuple[0])
p_tuple[0].set_alpha(0.4)
plt.savefig("val-error_sentiment-plot" + str(datetime.datetime.now()) + ".png", bbox_inches='tight') plt.savefig("val-error_sentiment-plot" + str(datetime.datetime.now()) + ".png", bbox_inches='tight')
# sentiment score axis # sentiment score axis
@ -105,6 +108,9 @@ def plot_sentiment_space(predicted_sentiment_vectors, top_sentiments, top_emojis
for i in range(len(top_X)): for i in range(len(top_X)):
plt.text(top_X[i], top_Y[i], top_emojis[i]) plt.text(top_X[i], top_Y[i], top_emojis[i])
plt.plot(pred_X, pred_Y, style) plt.plot(pred_X, pred_Y, style)
for p_tuple in additional_patches:
ax_2.add_artist(p_tuple[1])
p_tuple[1].set_alpha(0.4)
plt.savefig("val-error_positive-negative-plot" + str(datetime.datetime.now()) + ".png", bbox_inches='tight') plt.savefig("val-error_positive-negative-plot" + str(datetime.datetime.now()) + ".png", bbox_inches='tight')
plt.show() plt.show()