"Results in - zip file with set of json files containing:\n",
"<ul>\n",
"<li> feature matrix: data (raw countes), weighted (for example by mi-simple) and transform (by default equal to weighted)</li><li> distances and similarities between documents - calculated from transform.json using similarity/dictance metrix (cosine)</li>\n",
"\n"
]
},
{
{
"cell_type": "code",
"cell_type": "code",
"execution_count": 1,
"execution_count": 4,
"metadata": {},
"metadata": {},
"outputs": [
"outputs": [
{
{
"name": "stdout",
"name": "stdout",
"output_type": "stream",
"output_type": "stream",
"text": [
"text": [
"Uploaded with id /users/default/7a46fb4f-1639-4726-8ca7-55eb4ed4df93\n",
"Uploaded with id /users/default/e7064a0d-c756-4d3e-8a2c-4b0b72143f51\n",
Results in - zip file with set of json files containing:
<ul>
<li> feature matrix: data (raw countes), weighted (for example by mi-simple) and transform (by default equal to weighted)</li><li> distances and similarities between documents - calculated from transform.json using similarity/dictance metrix (cosine)</li>
%% Cell type:code id: tags:
%% Cell type:code id: tags:
``` python
``` python
importjson
importjson
importrequests
importrequests
importglob
importglob
importos
importos
importtime
importtime
user="mojadresemail@przyklad.pl"
user="mojadresemail@przyklad.pl"
#with document division into smaller parts - 20 kbytes
#with document division into smaller parts - 20 kbytes