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pushing files to the repo from the example!

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  1. NYC_SQF_ARR_RF_SMOTE.pkl +3 -0
  2. README.md +421 -0
  3. config.json +388 -0
NYC_SQF_ARR_RF_SMOTE.pkl ADDED
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+ version https://git-lfs.github.com/spec/v1
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+ oid sha256:0610bcfce7ef710b4f537c4905498f58d31e875f0172bd09b178302f04be2bd2
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+ size 33950490
README.md ADDED
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1
+ ---
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+ library_name: sklearn
3
+ tags:
4
+ - sklearn
5
+ - skops
6
+ - tabular-classification
7
+ model_format: pickle
8
+ model_file: NYC_SQF_ARR_RF_SMOTE.pkl
9
+ widget:
10
+ - structuredData:
11
+ ASK_FOR_CONSENT_FLG_(null):
12
+ - 0
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+ - 0
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+ - 0
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+ ASK_FOR_CONSENT_FLG_N:
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+ - 1
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+ - 1
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+ - 1
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+ ASK_FOR_CONSENT_FLG_Y:
20
+ - 0
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+ - 0
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+ - 0
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+ CONSENT_GIVEN_FLG_(null):
24
+ - 0
25
+ - 1
26
+ - 0
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+ CONSENT_GIVEN_FLG_N:
28
+ - 1
29
+ - 0
30
+ - 1
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+ CONSENT_GIVEN_FLG_Y:
32
+ - 0
33
+ - 0
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+ - 0
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+ FIREARM_FLAG:
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+ - 0
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+ - 0
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+ - 0
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+ FRISKED_FLAG:
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+ - 0
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+ - 1
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+ - 1
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+ ISSUING_OFFICER_RANK_CPT:
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+ - 0
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+ - 0
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+ - 0
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+ ISSUING_OFFICER_RANK_DI:
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+ - 0
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+ - 0
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+ - 0
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+ ISSUING_OFFICER_RANK_DT1:
52
+ - 0
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+ - 0
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+ - 0
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+ ISSUING_OFFICER_RANK_DT2:
56
+ - 0
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+ - 0
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+ - 0
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+ ISSUING_OFFICER_RANK_DT3:
60
+ - 0
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+ - 0
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+ - 0
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+ ISSUING_OFFICER_RANK_DTS:
64
+ - 0
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+ - 0
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+ - 0
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+ ISSUING_OFFICER_RANK_INS:
68
+ - 0
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+ - 0
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+ - 0
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+ ISSUING_OFFICER_RANK_LSA:
72
+ - 0
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+ - 0
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+ - 0
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+ ISSUING_OFFICER_RANK_LT:
76
+ - 0
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+ - 0
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+ - 0
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+ ISSUING_OFFICER_RANK_PO:
80
+ - 1
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+ - 1
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+ - 1
83
+ ISSUING_OFFICER_RANK_POF:
84
+ - 0
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+ - 0
86
+ - 0
87
+ ISSUING_OFFICER_RANK_POM:
88
+ - 0
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+ - 0
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+ - 0
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+ ISSUING_OFFICER_RANK_SDS:
92
+ - 0
93
+ - 0
94
+ - 0
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+ ISSUING_OFFICER_RANK_SGT:
96
+ - 0
97
+ - 0
98
+ - 0
99
+ ISSUING_OFFICER_RANK_SSA:
100
+ - 0
101
+ - 0
102
+ - 0
103
+ KNIFE_CUTTER_FLAG:
104
+ - 0
105
+ - 0
106
+ - 0
107
+ OTHER_CONTRABAND_FLAG:
108
+ - 0
109
+ - 0
110
+ - 0
111
+ OTHER_WEAPON_FLAG:
112
+ - 0
113
+ - 0
114
+ - 0
115
+ SEARCHED_FLAG:
116
+ - 0
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+ - 0
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+ - 1
119
+ STOP_LOCATION_PRECINCT:
120
+ - 20
121
+ - 23
122
+ - 46
123
+ SUPERVISING_OFFICER_RANK_CPT:
124
+ - 0
125
+ - 0
126
+ - 0
127
+ SUPERVISING_OFFICER_RANK_DI:
128
+ - 0
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+ - 0
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+ - 0
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+ SUPERVISING_OFFICER_RANK_DT3:
132
+ - 0
133
+ - 0
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+ - 0
135
+ SUPERVISING_OFFICER_RANK_DTS:
136
+ - 0
137
+ - 0
138
+ - 0
139
+ SUPERVISING_OFFICER_RANK_INS:
140
+ - 0
141
+ - 0
142
+ - 0
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+ SUPERVISING_OFFICER_RANK_LCD:
144
+ - 0
145
+ - 0
146
+ - 0
147
+ SUPERVISING_OFFICER_RANK_LSA:
148
+ - 0
149
+ - 0
150
+ - 0
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+ SUPERVISING_OFFICER_RANK_LT:
152
+ - 0
153
+ - 0
154
+ - 0
155
+ SUPERVISING_OFFICER_RANK_PO:
156
+ - 0
157
+ - 0
158
+ - 0
159
+ SUPERVISING_OFFICER_RANK_POF:
160
+ - 0
161
+ - 0
162
+ - 0
163
+ SUPERVISING_OFFICER_RANK_POM:
164
+ - 0
165
+ - 0
166
+ - 0
167
+ SUPERVISING_OFFICER_RANK_SDS:
168
+ - 0
169
+ - 0
170
+ - 0
171
+ SUPERVISING_OFFICER_RANK_SGT:
172
+ - 1
173
+ - 1
174
+ - 1
175
+ SUPERVISING_OFFICER_RANK_SSA:
176
+ - 0
177
+ - 0
178
+ - 0
179
+ SUSPECT_BODY_BUILD_TYPE_(null):
180
+ - 0
181
+ - 0
182
+ - 0
183
+ SUSPECT_BODY_BUILD_TYPE_HEA:
184
+ - 0
185
+ - 0
186
+ - 0
187
+ SUSPECT_BODY_BUILD_TYPE_MED:
188
+ - 0
189
+ - 1
190
+ - 1
191
+ SUSPECT_BODY_BUILD_TYPE_THN:
192
+ - 1
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+ - 0
194
+ - 0
195
+ SUSPECT_BODY_BUILD_TYPE_U:
196
+ - 0
197
+ - 0
198
+ - 0
199
+ SUSPECT_BODY_BUILD_TYPE_XXX:
200
+ - 0
201
+ - 0
202
+ - 0
203
+ SUSPECT_HEIGHT:
204
+ - 5.7
205
+ - 5.9
206
+ - 5.1
207
+ SUSPECT_RACE_DESCRIPTION_(null):
208
+ - 0
209
+ - 0
210
+ - 0
211
+ SUSPECT_RACE_DESCRIPTION_AMERICAN INDIAN/ALASKAN NATIVE:
212
+ - 0
213
+ - 0
214
+ - 0
215
+ SUSPECT_RACE_DESCRIPTION_ASIAN / PACIFIC ISLANDER:
216
+ - 0
217
+ - 0
218
+ - 0
219
+ SUSPECT_RACE_DESCRIPTION_BLACK:
220
+ - 0
221
+ - 0
222
+ - 1
223
+ SUSPECT_RACE_DESCRIPTION_BLACK HISPANIC:
224
+ - 0
225
+ - 0
226
+ - 0
227
+ SUSPECT_RACE_DESCRIPTION_MIDDLE EASTERN/SOUTHWEST ASIAN:
228
+ - 0
229
+ - 0
230
+ - 0
231
+ SUSPECT_RACE_DESCRIPTION_WHITE:
232
+ - 0
233
+ - 0
234
+ - 0
235
+ SUSPECT_RACE_DESCRIPTION_WHITE HISPANIC:
236
+ - 1
237
+ - 1
238
+ - 0
239
+ SUSPECT_REPORTED_AGE:
240
+ - 30.0
241
+ - 28.0
242
+ - 24.0
243
+ SUSPECT_SEX_(null):
244
+ - 0
245
+ - 0
246
+ - 0
247
+ SUSPECT_SEX_FEMALE:
248
+ - 0
249
+ - 0
250
+ - 0
251
+ SUSPECT_SEX_MALE:
252
+ - 1
253
+ - 1
254
+ - 1
255
+ SUSPECT_WEIGHT:
256
+ - 160.0
257
+ - 175.0
258
+ - 210.0
259
+ ---
260
+
261
+ # Model description
262
+
263
+ [More Information Needed]
264
+
265
+ ## Intended uses & limitations
266
+
267
+ [More Information Needed]
268
+
269
+ ## Training Procedure
270
+
271
+ [More Information Needed]
272
+
273
+ ### Hyperparameters
274
+
275
+ <details>
276
+ <summary> Click to expand </summary>
277
+
278
+ | Hyperparameter | Value |
279
+ |-------------------------------|-------------------------------------|
280
+ | memory | |
281
+ | steps | [('clf', RandomForestClassifier())] |
282
+ | verbose | False |
283
+ | clf | RandomForestClassifier() |
284
+ | clf__bootstrap | True |
285
+ | clf__ccp_alpha | 0.0 |
286
+ | clf__class_weight | |
287
+ | clf__criterion | gini |
288
+ | clf__max_depth | |
289
+ | clf__max_features | sqrt |
290
+ | clf__max_leaf_nodes | |
291
+ | clf__max_samples | |
292
+ | clf__min_impurity_decrease | 0.0 |
293
+ | clf__min_samples_leaf | 1 |
294
+ | clf__min_samples_split | 2 |
295
+ | clf__min_weight_fraction_leaf | 0.0 |
296
+ | clf__monotonic_cst | |
297
+ | clf__n_estimators | 100 |
298
+ | clf__n_jobs | |
299
+ | clf__oob_score | False |
300
+ | clf__random_state | |
301
+ | clf__verbose | 0 |
302
+ | clf__warm_start | False |
303
+
304
+ </details>
305
+
306
+ ### Model Plot
307
+
308
+ <style>#sk-container-id-1 {/* Definition of color scheme common for light and dark mode */--sklearn-color-text: black;--sklearn-color-line: gray;/* Definition of color scheme for unfitted estimators */--sklearn-color-unfitted-level-0: #fff5e6;--sklearn-color-unfitted-level-1: #f6e4d2;--sklearn-color-unfitted-level-2: #ffe0b3;--sklearn-color-unfitted-level-3: chocolate;/* Definition of color scheme for fitted estimators */--sklearn-color-fitted-level-0: #f0f8ff;--sklearn-color-fitted-level-1: #d4ebff;--sklearn-color-fitted-level-2: #b3dbfd;--sklearn-color-fitted-level-3: cornflowerblue;/* Specific color for light theme */--sklearn-color-text-on-default-background: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, black)));--sklearn-color-background: var(--sg-background-color, var(--theme-background, var(--jp-layout-color0, white)));--sklearn-color-border-box: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, black)));--sklearn-color-icon: #696969;@media (prefers-color-scheme: dark) {/* Redefinition of color scheme for dark theme */--sklearn-color-text-on-default-background: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, white)));--sklearn-color-background: var(--sg-background-color, var(--theme-background, var(--jp-layout-color0, #111)));--sklearn-color-border-box: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, white)));--sklearn-color-icon: #878787;}
309
+ }#sk-container-id-1 {color: var(--sklearn-color-text);
310
+ }#sk-container-id-1 pre {padding: 0;
311
+ }#sk-container-id-1 input.sk-hidden--visually {border: 0;clip: rect(1px 1px 1px 1px);clip: rect(1px, 1px, 1px, 1px);height: 1px;margin: -1px;overflow: hidden;padding: 0;position: absolute;width: 1px;
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+ }#sk-container-id-1 div.sk-dashed-wrapped {border: 1px dashed var(--sklearn-color-line);margin: 0 0.4em 0.5em 0.4em;box-sizing: border-box;padding-bottom: 0.4em;background-color: var(--sklearn-color-background);
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+ }#sk-container-id-1 div.sk-container {/* jupyter's `normalize.less` sets `[hidden] { display: none; }`but bootstrap.min.css set `[hidden] { display: none !important; }`so we also need the `!important` here to be able to override thedefault hidden behavior on the sphinx rendered scikit-learn.org.See: https://github.com/scikit-learn/scikit-learn/issues/21755 */display: inline-block !important;position: relative;
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+ }#sk-container-id-1 div.sk-text-repr-fallback {display: none;
315
+ }div.sk-parallel-item,
316
+ div.sk-serial,
317
+ div.sk-item {/* draw centered vertical line to link estimators */background-image: linear-gradient(var(--sklearn-color-text-on-default-background), var(--sklearn-color-text-on-default-background));background-size: 2px 100%;background-repeat: no-repeat;background-position: center center;
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+ }/* Parallel-specific style estimator block */#sk-container-id-1 div.sk-parallel-item::after {content: "";width: 100%;border-bottom: 2px solid var(--sklearn-color-text-on-default-background);flex-grow: 1;
319
+ }#sk-container-id-1 div.sk-parallel {display: flex;align-items: stretch;justify-content: center;background-color: var(--sklearn-color-background);position: relative;
320
+ }#sk-container-id-1 div.sk-parallel-item {display: flex;flex-direction: column;
321
+ }#sk-container-id-1 div.sk-parallel-item:first-child::after {align-self: flex-end;width: 50%;
322
+ }#sk-container-id-1 div.sk-parallel-item:last-child::after {align-self: flex-start;width: 50%;
323
+ }#sk-container-id-1 div.sk-parallel-item:only-child::after {width: 0;
324
+ }/* Serial-specific style estimator block */#sk-container-id-1 div.sk-serial {display: flex;flex-direction: column;align-items: center;background-color: var(--sklearn-color-background);padding-right: 1em;padding-left: 1em;
325
+ }/* Toggleable style: style used for estimator/Pipeline/ColumnTransformer box that is
326
+ clickable and can be expanded/collapsed.
327
+ - Pipeline and ColumnTransformer use this feature and define the default style
328
+ - Estimators will overwrite some part of the style using the `sk-estimator` class
329
+ *//* Pipeline and ColumnTransformer style (default) */#sk-container-id-1 div.sk-toggleable {/* Default theme specific background. It is overwritten whether we have aspecific estimator or a Pipeline/ColumnTransformer */background-color: var(--sklearn-color-background);
330
+ }/* Toggleable label */
331
+ #sk-container-id-1 label.sk-toggleable__label {cursor: pointer;display: block;width: 100%;margin-bottom: 0;padding: 0.5em;box-sizing: border-box;text-align: center;
332
+ }#sk-container-id-1 label.sk-toggleable__label-arrow:before {/* Arrow on the left of the label */content: "▸";float: left;margin-right: 0.25em;color: var(--sklearn-color-icon);
333
+ }#sk-container-id-1 label.sk-toggleable__label-arrow:hover:before {color: var(--sklearn-color-text);
334
+ }/* Toggleable content - dropdown */#sk-container-id-1 div.sk-toggleable__content {max-height: 0;max-width: 0;overflow: hidden;text-align: left;/* unfitted */background-color: var(--sklearn-color-unfitted-level-0);
335
+ }#sk-container-id-1 div.sk-toggleable__content.fitted {/* fitted */background-color: var(--sklearn-color-fitted-level-0);
336
+ }#sk-container-id-1 div.sk-toggleable__content pre {margin: 0.2em;border-radius: 0.25em;color: var(--sklearn-color-text);/* unfitted */background-color: var(--sklearn-color-unfitted-level-0);
337
+ }#sk-container-id-1 div.sk-toggleable__content.fitted pre {/* unfitted */background-color: var(--sklearn-color-fitted-level-0);
338
+ }#sk-container-id-1 input.sk-toggleable__control:checked~div.sk-toggleable__content {/* Expand drop-down */max-height: 200px;max-width: 100%;overflow: auto;
339
+ }#sk-container-id-1 input.sk-toggleable__control:checked~label.sk-toggleable__label-arrow:before {content: "▾";
340
+ }/* Pipeline/ColumnTransformer-specific style */#sk-container-id-1 div.sk-label input.sk-toggleable__control:checked~label.sk-toggleable__label {color: var(--sklearn-color-text);background-color: var(--sklearn-color-unfitted-level-2);
341
+ }#sk-container-id-1 div.sk-label.fitted input.sk-toggleable__control:checked~label.sk-toggleable__label {background-color: var(--sklearn-color-fitted-level-2);
342
+ }/* Estimator-specific style *//* Colorize estimator box */
343
+ #sk-container-id-1 div.sk-estimator input.sk-toggleable__control:checked~label.sk-toggleable__label {/* unfitted */background-color: var(--sklearn-color-unfitted-level-2);
344
+ }#sk-container-id-1 div.sk-estimator.fitted input.sk-toggleable__control:checked~label.sk-toggleable__label {/* fitted */background-color: var(--sklearn-color-fitted-level-2);
345
+ }#sk-container-id-1 div.sk-label label.sk-toggleable__label,
346
+ #sk-container-id-1 div.sk-label label {/* The background is the default theme color */color: var(--sklearn-color-text-on-default-background);
347
+ }/* On hover, darken the color of the background */
348
+ #sk-container-id-1 div.sk-label:hover label.sk-toggleable__label {color: var(--sklearn-color-text);background-color: var(--sklearn-color-unfitted-level-2);
349
+ }/* Label box, darken color on hover, fitted */
350
+ #sk-container-id-1 div.sk-label.fitted:hover label.sk-toggleable__label.fitted {color: var(--sklearn-color-text);background-color: var(--sklearn-color-fitted-level-2);
351
+ }/* Estimator label */#sk-container-id-1 div.sk-label label {font-family: monospace;font-weight: bold;display: inline-block;line-height: 1.2em;
352
+ }#sk-container-id-1 div.sk-label-container {text-align: center;
353
+ }/* Estimator-specific */
354
+ #sk-container-id-1 div.sk-estimator {font-family: monospace;border: 1px dotted var(--sklearn-color-border-box);border-radius: 0.25em;box-sizing: border-box;margin-bottom: 0.5em;/* unfitted */background-color: var(--sklearn-color-unfitted-level-0);
355
+ }#sk-container-id-1 div.sk-estimator.fitted {/* fitted */background-color: var(--sklearn-color-fitted-level-0);
356
+ }/* on hover */
357
+ #sk-container-id-1 div.sk-estimator:hover {/* unfitted */background-color: var(--sklearn-color-unfitted-level-2);
358
+ }#sk-container-id-1 div.sk-estimator.fitted:hover {/* fitted */background-color: var(--sklearn-color-fitted-level-2);
359
+ }/* Specification for estimator info (e.g. "i" and "?") *//* Common style for "i" and "?" */.sk-estimator-doc-link,
360
+ a:link.sk-estimator-doc-link,
361
+ a:visited.sk-estimator-doc-link {float: right;font-size: smaller;line-height: 1em;font-family: monospace;background-color: var(--sklearn-color-background);border-radius: 1em;height: 1em;width: 1em;text-decoration: none !important;margin-left: 1ex;/* unfitted */border: var(--sklearn-color-unfitted-level-1) 1pt solid;color: var(--sklearn-color-unfitted-level-1);
362
+ }.sk-estimator-doc-link.fitted,
363
+ a:link.sk-estimator-doc-link.fitted,
364
+ a:visited.sk-estimator-doc-link.fitted {/* fitted */border: var(--sklearn-color-fitted-level-1) 1pt solid;color: var(--sklearn-color-fitted-level-1);
365
+ }/* On hover */
366
+ div.sk-estimator:hover .sk-estimator-doc-link:hover,
367
+ .sk-estimator-doc-link:hover,
368
+ div.sk-label-container:hover .sk-estimator-doc-link:hover,
369
+ .sk-estimator-doc-link:hover {/* unfitted */background-color: var(--sklearn-color-unfitted-level-3);color: var(--sklearn-color-background);text-decoration: none;
370
+ }div.sk-estimator.fitted:hover .sk-estimator-doc-link.fitted:hover,
371
+ .sk-estimator-doc-link.fitted:hover,
372
+ div.sk-label-container:hover .sk-estimator-doc-link.fitted:hover,
373
+ .sk-estimator-doc-link.fitted:hover {/* fitted */background-color: var(--sklearn-color-fitted-level-3);color: var(--sklearn-color-background);text-decoration: none;
374
+ }/* Span, style for the box shown on hovering the info icon */
375
+ .sk-estimator-doc-link span {display: none;z-index: 9999;position: relative;font-weight: normal;right: .2ex;padding: .5ex;margin: .5ex;width: min-content;min-width: 20ex;max-width: 50ex;color: var(--sklearn-color-text);box-shadow: 2pt 2pt 4pt #999;/* unfitted */background: var(--sklearn-color-unfitted-level-0);border: .5pt solid var(--sklearn-color-unfitted-level-3);
376
+ }.sk-estimator-doc-link.fitted span {/* fitted */background: var(--sklearn-color-fitted-level-0);border: var(--sklearn-color-fitted-level-3);
377
+ }.sk-estimator-doc-link:hover span {display: block;
378
+ }/* "?"-specific style due to the `<a>` HTML tag */#sk-container-id-1 a.estimator_doc_link {float: right;font-size: 1rem;line-height: 1em;font-family: monospace;background-color: var(--sklearn-color-background);border-radius: 1rem;height: 1rem;width: 1rem;text-decoration: none;/* unfitted */color: var(--sklearn-color-unfitted-level-1);border: var(--sklearn-color-unfitted-level-1) 1pt solid;
379
+ }#sk-container-id-1 a.estimator_doc_link.fitted {/* fitted */border: var(--sklearn-color-fitted-level-1) 1pt solid;color: var(--sklearn-color-fitted-level-1);
380
+ }/* On hover */
381
+ #sk-container-id-1 a.estimator_doc_link:hover {/* unfitted */background-color: var(--sklearn-color-unfitted-level-3);color: var(--sklearn-color-background);text-decoration: none;
382
+ }#sk-container-id-1 a.estimator_doc_link.fitted:hover {/* fitted */background-color: var(--sklearn-color-fitted-level-3);
383
+ }
384
+ </style><div id="sk-container-id-1" class="sk-top-container" style="overflow: auto;"><div class="sk-text-repr-fallback"><pre>Pipeline(steps=[(&#x27;clf&#x27;, RandomForestClassifier())])</pre><b>In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook. <br />On GitHub, the HTML representation is unable to render, please try loading this page with nbviewer.org.</b></div><div class="sk-container" hidden><div class="sk-item sk-dashed-wrapped"><div class="sk-label-container"><div class="sk-label fitted sk-toggleable"><input class="sk-toggleable__control sk-hidden--visually" id="sk-estimator-id-1" type="checkbox" ><label for="sk-estimator-id-1" class="sk-toggleable__label fitted sk-toggleable__label-arrow fitted">&nbsp;&nbsp;Pipeline<a class="sk-estimator-doc-link fitted" rel="noreferrer" target="_blank" href="https://scikit-learn.org/1.5/modules/generated/sklearn.pipeline.Pipeline.html">?<span>Documentation for Pipeline</span></a><span class="sk-estimator-doc-link fitted">i<span>Fitted</span></span></label><div class="sk-toggleable__content fitted"><pre>Pipeline(steps=[(&#x27;clf&#x27;, RandomForestClassifier())])</pre></div> </div></div><div class="sk-serial"><div class="sk-item"><div class="sk-estimator fitted sk-toggleable"><input class="sk-toggleable__control sk-hidden--visually" id="sk-estimator-id-2" type="checkbox" ><label for="sk-estimator-id-2" class="sk-toggleable__label fitted sk-toggleable__label-arrow fitted">&nbsp;RandomForestClassifier<a class="sk-estimator-doc-link fitted" rel="noreferrer" target="_blank" href="https://scikit-learn.org/1.5/modules/generated/sklearn.ensemble.RandomForestClassifier.html">?<span>Documentation for RandomForestClassifier</span></a></label><div class="sk-toggleable__content fitted"><pre>RandomForestClassifier()</pre></div> </div></div></div></div></div></div>
385
+
386
+ ## Evaluation Results
387
+
388
+ | Metric | Value |
389
+ |-----------|----------|
390
+ | accuracy | 0.852071 |
391
+ | f1 score | 0.763033 |
392
+ | precision | 0.786325 |
393
+ | recall | 0.741082 |
394
+
395
+ # How to Get Started with the Model
396
+
397
+ [More Information Needed]
398
+
399
+ # Model Card Authors
400
+
401
+ This model card is written by following authors:
402
+
403
+ [More Information Needed]
404
+
405
+ # Model Card Contact
406
+
407
+ You can contact the model card authors through following channels:
408
+ [More Information Needed]
409
+
410
+ # Citation
411
+
412
+ Below you can find information related to citation.
413
+
414
+ **BibTeX:**
415
+ ```
416
+ [More Information Needed]
417
+ ```
418
+
419
+ # eval_method
420
+
421
+ The model is evaluated using test split, on accuracy, precision, recall and f1.
config.json ADDED
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+ "model": {
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+ "file": "NYC_SQF_ARR_RF_SMOTE.pkl"
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+ },
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+ "model_format": "pickle",
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+ "task": "tabular-classification"
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+ }
388
+ }